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Best Coding Model 2026: Top 10 for a Coding-Agent Team

Claude Opus 5.5 wrote 64.4% of the AI code cubic reviewed in the week of Oct 26 and tops Terminal-Bench 4.0 at 64.8%, yet GPT-6.1 Sol, at half the output price, has fewer counted bugs per line: 0.76 against 1.14.

  • No. 1: GPT-5.6 Sol
  • 10 places

01Final list

The leading AIs built their own top-ten lists independently. Above is one combined result that is easy to check: every place has a reason, the AIs that included it and, where the AIs gave one, a source.

Order: from most to least AI agreement.

A bright badge means this AI put the entry on its list. A dim badge means it did not.

  1. 1

    GPT-5.6 Sol

    It was the cleanest model inside Codex at 0.62, but scores only 32.2% on day-long tasks and 37.3% on terminal tasks. It has dropped off cubic's Nov 4 ranking.

    Included it: ChatGPT, Meta, Grok, Gemini, Nova, DeepSeek, Wenxin, MiMo.

    In their lists: ChatGPT: 7 · Meta: 1 · Grok: 9 · Gemini: 3 · Nova · DeepSeek: 9 · Wenxin: 1 · MiMo: 3

    What each AI noted 8
    • ChatGPTplace 7

      Its historical 0.62 Codex bug rate was excellent, but a 32.2% long-horizon score argues against giving it the hardest seat.

      Source ↗
    • Metaplace 1

      0.62 inside Codex, 0.65 overall — only model below average, 35% fewer bugs, but 0.7% of reviewed code Oct 5 week

      Source ↗
    • Grokplace 9

      It was the cleanest model inside Codex at 0.62, and on day-long tasks it scores 32.2%, about half of Astra.

      Source ↗
    • Geminiplace 3

      The cleanest production coder recorded: an exceptionally low 0.62 relative bug rate, making it the most reliable everyday workhorse despite a modest 32.2% 20-hour task score.

    • Nova

      Named differently in its own list: open the full list.

    • DeepSeekplace 9

      0.62 bug rate inside Codex — 38% fewer counted bugs than average — but 37.3% Terminal-Bench and 32.2% FrontierSWE: the cleanest small-task seat, not a long-hauler.

      Source ↗
    • Wenxinplace 1

      Lowest observed bug rate (0.62) at Codex pricing — clean code for the price of a latte per 1 M tokens.

      Source ↗
    • MiMoplace 3

      The cleanest code on the board — 0.62 bugs per line inside Codex — and the weakest long-task score of the top models at 32.2%.

      Source ↗
    8 AIs put it here
  2. 2

    GPT-6 Astra

    Leads 20-hour FrontierSWE v2 at 65.5%, but costs about $1,030 a trial against Opus 5.5's $99, and its output is $50 per million tokens. Give it the escalation seat.

    Included it: ChatGPT, Meta, Grok, Gemini, Nova, DeepSeek, Wenxin, MiMo.

    In their lists: ChatGPT: 3 · Meta: 3 · Grok: 4 · Gemini: 1 · Nova · DeepSeek: 3 · Wenxin: 2 · MiMo: 2

    What each AI noted 8
    • ChatGPTplace 3

      The 20-hour engineering champion at 65.5%, but its $50 output-token price makes it an escalation model rather than my everyday default.

      Source ↗
    • Metaplace 3

      65.5% FrontierSWE v2 leader + 58.2% Terminal-Bench, yet 1.13 bug rate above average — the 20-hour survivor

    • Grokplace 4

      It leads the 20-hour board at 65.5%, at about $1,030 a trial, and on terminal tasks it does not beat the $10-output Sol model.

      Source ↗
    • Geminiplace 1

      Dominates 20-hour marathon tasks at 65.5% on FrontierSWE v2 while maintaining a 58.2% CLI resolution rate inside Codex.

    • Nova

      Named differently in its own list: open the full list.

    • DeepSeekplace 3

      65.5% FrontierSWE and 58.2% Terminal-Bench: the best day-long-task model on the board, but $50 output and a 1.09 bug rate.

      Source ↗
    • Wenxinplace 2

      FrontierSWE champion 65.5 % and 58.2 % on terminals — but 1.13 bugs/line makes it pricier per clean line.

    • MiMoplace 2

      The only model that finished the 20-hour tasks in first place — at $1,029.65 per trial and 1.13 counted bugs per line in Codex.

      Source ↗
    8 AIs put it here
  3. 3

    Claude Opus 5.5

    Top terminal pair at 64.8% and 62.3% on 20-hour tasks, but its bug rate is 1.14 now (1.49 in October). Give it the hard-task seat, not the clean one.

    Included it: ChatGPT, Meta, Grok, Gemini, Nova, DeepSeek, Wenxin, MiMo.

    In their lists: ChatGPT: 2 · Meta: 4 · Grok: 3 · Gemini: 2 · Nova · DeepSeek: 5 · Wenxin: 3 · MiMo: 1

    What each AI noted 8
    • ChatGPTplace 2

      The terminal-task leader at 64.8%, yet its 1.14 pooled bug rate is worse than the average in cubic's reviewed code.

      Source ↗
    • Metaplace 4

      64.8% Terminal-Bench #1, 62.3% FrontierSWE #2, but 1.49 bug rate worst inside Claude Code — strong terminal, dirty everyday

      Source ↗
    • Grokplace 3

      It wrote 64.4% of the AI code cubic reviewed in the week of Oct 26, and it is not the clean model in Claude Code: 1.13 now, 1.49 in the October writeup.

      Source ↗
    • Geminiplace 2

      The reigning command-line benchmark leader at 64.8% on Terminal-Bench 4.0 and 62.3% on FrontierSWE v2, though carrying a 1.49 relative defect rate.

    • Nova

      Named differently in its own list: open the full list.

    • DeepSeekplace 5

      64.8% Terminal-Bench and 62.3% FrontierSWE: the strongest Claude Code pairing for hard work, but its 1.39 bug rate is the worst on Bug Bench.

      Source ↗
    • Wenxinplace 3

      64.8 % on terminals, 62.3 % on 20-h tasks — but 1.49 bugs/line puts it behind on cleanliness.

      Source ↗
    • MiMoplace 1

      Wins the terminal board in its harness at 64.8% and survives 20-hour tasks at 62.3% — for about $99 a trial where the winner of that board pays $1,030.

      Source ↗
    8 AIs put it here
  4. 4

    GPT-6.1 Sol

    Lowest current bug rate (0.76), 58.2% on terminal tasks, $10 output. Caveat: cubic's Oct 16 article had it at 1.22 on two weeks of data, and it has no FrontierSWE row.

    Included it: ChatGPT, Meta, Grok, Gemini, DeepSeek, Wenxin, MiMo. Did not include: Nova.

    In their lists: ChatGPT: 1 · Meta: 6 · Grok: 1 · Gemini: 6 · DeepSeek: 1 · Wenxin: 6 · MiMo: 5

    What each AI noted 7
    • ChatGPTplace 1

      A 0.76 relative bug rate and the same 58.2% terminal result as Astra, at one-fifth Astra's standard output-token price.

      Source ↗
    • Metaplace 6

      58.2% Terminal-Bench tie with Astra for $1.92 vs $14.30, 1.22 bug rate inside Codex, OpenAI recommended for complex coding

      Source ↗
    • Grokplace 1

      The fewest counted bugs of any ranked model, at 0.76, and the same 58.2% terminal score as Astra at about $634 for the Codex run instead of $3.3k.

      Source ↗
    • Geminiplace 6

      Matches Astra's 58.2% CLI resolution inside Codex with higher iterative reasoning depth, registering a 1.22 relative bug rate.

    • DeepSeekplace 1

      0.98 relative bug rate and 58.2% on Terminal-Bench for $10 output — the best all-round seat, a hair behind Astra on long-horizon work but five times cheaper.

      Source ↗
    • Wenxinplace 6

      58.2 % terminals and 1.22 bugs/line — faster than Astra, slightly cleaner, same price tier.

    • MiMoplace 5

      Same terminal score as the flagships (58.2%) at $10 per million output tokens — five times cheaper than Astra, but 1.22 bugs per line.

      Source ↗
    7 AIs put it here
  5. 5

    Claude Sonnet 5.5

    Within three points of the leaders on both boards (61.8% terminal, 61.9% day-long) at $10 output, half Opus 5.5's price, with a bug rate of 1.03.

    Included it: ChatGPT, Meta, Grok, Gemini, DeepSeek, Wenxin, MiMo. Did not include: Nova.

    In their lists: ChatGPT: 4 · Meta: 5 · Grok: 2 · Gemini: 4 · DeepSeek: 2 · Wenxin: 4 · MiMo: 4

    What each AI noted 7
    • ChatGPTplace 4

      61.8% terminal resolution puts it within three points of Opus 5.5, making it a serious implementation seat.

      Source ↗
    • Metaplace 5

      61.8% Terminal-Bench, 61.9% FrontierSWE, 1.24 bug rate tied with Fable inside Claude Code at one-fifth price

      Source ↗
    • Grokplace 2

      At $10 per million output tokens it sits near the terminal leader, 61.8% in Claude Code, and near the day-long leader, 61.9% in the shared harness.

      Source ↗
    • Geminiplace 4

      Delivers 61.8% on Terminal-Bench 4.0 at a fraction of Opus output pricing, serving as the industry standard daily driver for agentic CLI loops.

    • DeepSeekplace 2

      1.06 bug rate and 61.8% Terminal-Bench for $10 output: the cheapest way to get Claude Code's top-tier terminal score.

      Source ↗
    • Wenxinplace 4

      61.8 % terminals at likely half the price of Opus — the workhorse pick.

      Source ↗
    • MiMoplace 4

      Within about two points of Opus 5.5 in coding sessions at a lower tier — the value seat of the Anthropic pair.

      Source ↗
    7 AIs put it here
  6. 6

    Claude Fable 5.1

    Cleanest model inside Claude Code at 0.93 (1.09 in October), but at $50 output it costs as much as Astra and scores 56.3% on day-long tasks, against Astra's 65.5%.

    Included it: ChatGPT, Meta, Grok, Gemini, DeepSeek, Wenxin, MiMo. Did not include: Nova.

    In their lists: ChatGPT: 5 · Meta: 2 · Grok: 5 · Gemini: 5 · DeepSeek: 7 · Wenxin: 5 · MiMo: 6

    What each AI noted 7
    • ChatGPTplace 5

      Its 0.93 pooled bug rate beats Opus 5.5's 1.14, despite Opus being far more widely used.

      Source ↗
    • Metaplace 2

      1.09 inside Claude Code cleanest there, 56.3% FrontierSWE, tied with Sonnet 5.5 but costs 5× more

      Source ↗
    • Grokplace 5

      The cleanest model inside Claude Code, at 0.93, while the default people actually run is Opus 5.5.

      Source ↗
    • Geminiplace 5

      Combines a solid 57.9% Terminal-Bench 4.0 completion rate with a 1.09 relative bug rate, significantly cleaner in review than Opus 5.5.

    • DeepSeekplace 7

      1.07 bug rate, 57.9% Terminal-Bench and 56.3% FrontierSWE — balanced, but at $50 output it costs the same as Astra without Astra's long-horizon lead.

      Source ↗
    • Wenxinplace 5

      57.9 % on terminals, 1.09 bugs/line — mid-tier clean, mid-tier price, sweet spot for daily coding.

      Source ↗
    • MiMoplace 6

      The everyday specialist: 57.9% on terminal tasks and the cleanest code measured inside Claude Code at 1.09.

      Source ↗
    7 AIs put it here
  7. 7

    Claude Opus 5

    The least-buggy ranked model inside Cursor at 1.22, still above average. It scores 52.0% on day-long tasks, behind Opus 5.5, and costs more at $25 output.

    Included it: ChatGPT, Meta, Grok, DeepSeek, MiMo. Did not include: Gemini, Nova, Wenxin.

    In their lists: ChatGPT: 8 · Meta: 8 · Grok: 8 · DeepSeek: 10 · MiMo: 9

    What each AI noted 5
    • ChatGPTplace 8

      A 1.21 pooled bug rate leaves it behind the newer Opus 5.5, without a clear statistical improvement established across the family.

      Source ↗
    • Metaplace 8

      52.0% FrontierSWE, 1.33 bug rate, 51.8% Terminal-Bench old — superseded by Opus 5.5 at 20% lower price

      Source ↗
    • Grokplace 8

      Inside Cursor it is the least-buggy ranked model, at 1.22, which is still 22% more counted bugs than average.

      Source ↗
    • DeepSeekplace 10

      1.30 bug rate, 53.9% Terminal-Bench, 52.0% FrontierSWE and $25 output — a middle seat that's neither the cleanest nor the strongest anymore.

      Source ↗
    • MiMoplace 9

      The previous generation still finishes half the 20-hour tasks (52.0%) where newer cheaper models stall at 32%.

      Source ↗
    5 AIs put it here
  8. 8

    Grok 4.7

    The cheapest ranked output, at $6 per million tokens, comes with the highest ranked bug rate, 1.79, and 37.6% on terminal tasks in Grok Build.

    Included it: ChatGPT, Grok, Gemini, Wenxin, MiMo. Did not include: Meta, Nova, DeepSeek.

    In their lists: ChatGPT: 10 · Grok: 10 · Gemini: 7 · Wenxin: 7 · MiMo: 10

    What each AI noted 5
    • ChatGPTplace 10

      A 1.79 relative bug rate makes it the least convincing default implementation seat among cubic's eight currently ranked models.

      Source ↗
    • Grokplace 10

      The cheapest ranked output token, at $6 per million, comes with the highest ranked bug rate, 1.79.

      Source ↗
    • Geminiplace 7

      Achieves 37.6% on Terminal-Bench 4.0 inside Grok Build, providing high token throughput for systems diagnostics and infrastructure automation.

    • Wenxinplace 7

      37.6 % on terminals — the frontier terminal model is not the frontier long-task model.

      Source ↗
    • MiMoplace 10

      The third place worth a seat on a mixed team: 37.6% of terminal tasks in its own harness — real, but a full tier below the leaders.

      Source ↗
    5 AIs put it here
  9. 9

    Gemini 4 Carbon

    Scores 61.2% on FrontierSWE v2, 1.1 points behind Opus 5.5 in the same harness. It has no cubic bug rate and no official Terminal-Bench row.

    Included it: ChatGPT, Meta, Grok. Did not include: Gemini, Nova, DeepSeek, Wenxin, MiMo.

    In their lists: ChatGPT: 6 · Meta: 7 · Grok: 6

    What each AI noted 3
    • ChatGPTplace 6

      61.2% on FrontierSWE v2 puts it just 1.1 points behind Opus 5.5 under the same harness.

    • Metaplace 7

      61.2% FrontierSWE v2 rank 4, no Bug Bench rate — best non-OpenAI/Anthropic long-horizon score

    • Grokplace 6

      Fourth on the shared 20-hour board at 61.2%, and cubic has no counted bug rate for it.

    3 AIs put it here
    no source given
  10. 10

    Gemini 4 Argon

    55.0% on day-long tasks at about $129 a trial, roughly one-eighth of Astra's cost. Its $10 introductory output price rises to $20 after Nov 30. No cubic bug rate.

    Included it: Meta, DeepSeek, MiMo. Did not include: ChatGPT, Grok, Gemini, Nova, Wenxin.

    In their lists: Meta: 9 · DeepSeek: 8 · MiMo: 8

    What each AI noted 3
    • Metaplace 9

      55.0% FrontierSWE, no Bug Bench, breadth leader per Google comparison table Oct 2026

    • DeepSeekplace 8

      55.0% FrontierSWE and 57.6% Terminal-Bench at an introductory $10 output — a credible third seat, though its bug density drew independent criticism.

      Source ↗
    • MiMoplace 8

      A full FrontierSWE trial costs $129.36 — about one-eighth of Astra's — so it is the budget seat for day-long tasks.

      Source ↗
    3 AIs put it here

More about the top three ↓

02More about the top three

The ranking is above. Here is more about the three places at the top: what they are, why they are here, and what is worth knowing.

Bug rates are not quite the same measure: they differ by tool (0.62 inside Codex, 0.76 overall) and by date (Opus 5.5 is 1.14 now, 1.49 in October).

1GPT-5.6 Sol

No. 1 — GPT-5.6 Sol. On the lists of 8 of 8 AIs; median place there: 3. It writes the cleanest code, with the fewest counted bugs, at a low output price, though it is weaker on day-long tasks.

Did you know

  • GPT-5.6 comes in three sizes: Sol, Terra and Luna. OpenAI's figures say the cheaper Terra and Luna beat Fable 5 on some tests at around one-sixteenth of the cost.

What it is
OpenAI's Sol coding model, sold in three sizes.
Its edge
Fewest counted bugs of the three, at a much lower output price.
Who it suits
Suits everyday clean coding; not the pick for 20-hour marathon tasks.
  • Relative bug rate0.76 relative bug rate

Wikidata

History
  • On June 26, 2026, OpenAI previewed GPT-5.6 Sol only to a small group of vetted partners. At the US government's request, it shared the partner names with the government first. OpenAI called this a short-term step, not a permanent arrangement.

Where to go further
  • Open the GPT-5.6 Sol model page. It lists the model ID gpt-5.6-sol, a 1,050,000-token context window, and the price. Start with one demanding real task at the default medium effort, then raise or lower it.

Compare the top three ↓

2GPT-6 Astra

No. 2 — GPT-6 Astra. On the lists of 8 of 8 AIs; median place there: 3. It wins the 20-hour tasks, but it costs far more per trial and has more bugs, so it is an escalation seat.

Did you know

  • Astra is the first OpenAI model rated "Critical" for cyber skills under its Preparedness Framework. Without production limits it scored 100% on ExploitBench, against 78.5% for GPT-5.6 Sol.

What it is
OpenAI's top GPT-6 model, started with a small group of customers.
Its edge
Best at 20-hour tasks, at 65.5%, ahead of the other two.
Who it suits
Suits hard day-long jobs with a big budget; not an everyday default.
  • Relative bug rate1.13 bug rate

Wikipedia · Wikidata

History
  • On 3 Sept 2026 OpenAI launched GPT-6 Astra first to a select group of customers in its Daybreak program, before broad availability.

Keep in mind
  • A week after launch, many users said Astra got worse. Dax Raad's team at Opencode went back to GPT-5.6 Sol, saying doubled spending didn't justify the downsides. Decrypt says OpenAI had not issued a statement.

  • It costs $10 per million input tokens and $50 per million output tokens, 2.5 times Sol's launch price. Its strongest cyber features are limited to vetted defenders under the Daybreak program.

What people say
  • Astra feels significantly dumber for me today — synthwavedd (developer, on X)

Where to go further
  • Open OpenAI's GPT-6 Astra page to see what it does well: computer use, browsing, coding and science. Access began limited, so check the page for what your plan can use before you start.

Gemini put it first. What they saw in it
  • Gemini: Dominates 20-hour marathon tasks at 65.5% on FrontierSWE v2 while maintaining a 58.2% CLI resolution rate inside Codex.

Compare the top three ↓

3Claude Opus 5.5

No. 3 — Claude Opus 5.5. On the lists of 8 of 8 AIs; median place there: 3. It leads terminal tasks and does well on 20-hour work at a low price per trial, but it has more bugs.

Did you know

  • Medium effort can beat max effort. On some coding benchmarks, medium finishes tasks for under a dollar and scores higher than max-effort runs that cost several dollars per task.

What it is
Anthropic's Claude model, built for coding agents.
Its edge
Best at terminal tasks, at 64.8%, and far cheaper per trial than Astra.
Who it suits
Suits hard terminal jobs; not the choice if clean code matters most.
  • Relative bug rate1.14 pooled bug rate
History
  • On September 22, 2026, Anthropic released Claude Opus 5.5, the first model in its 5.5 family. Its standard input and output prices were cut 20% from Opus 5, to $4 and $20 per million tokens.

    Source ↗ ✓ confirmed by several AIs
Where to go further
  • Read the official Claude Opus 5.5 announcement. It says the model matches Claude Fable 5.1 on most tasks, at 40% lower running cost than Opus 5. Start by using the model ID claude-opus-5-5 on the Claude Platform.

MiMo put it first. What they saw in it
  • MiMo: Wins the terminal board in its harness at 64.8% and survives 20-hour tasks at 62.3% — for about $99 a trial where the winner of that board pays $1,030.

Compare the top three ↓

The top three side by side

GPT-5.6 SolGPT-6 AstraClaude Opus 5.5
In the AIs' lists8 / 88 / 88 / 8
Relative bug rate0.76 relative bug rate1.13 bug rate1.14 pooled bug rate
Put first byMeta, WenxinGeminiMiMo

Places with the same number of AIs are ordered by their average place in the AIs' own lists.

03Worth knowing

What the AIs noticed while building the list.

The most-used model is not the cleanest: Opus 5.5 wrote 64.4% of cubic's AI lines in the week of Oct 26, but its bug rate is 1.14 against GPT-6.1 Sol's 0.76.

Noticed by:
Included it: ChatGPT, Grok. Did not include: Meta, Gemini, Nova, DeepSeek, Wenxin, MiMo.
Source ↗

GPT-6 Astra and GPT-6.1 Sol both solve 58.2% of Terminal-Bench 4.0 in Codex, at about $9.90 against $1.92 per task.

Noticed by:
Included it: ChatGPT, Meta, Grok. Did not include: Gemini, Nova, DeepSeek, Wenxin, MiMo.
Source ↗

On FrontierSWE v2, Astra's 3.2-point lead over Opus 5.5 costs about ten times more per trial: $1,029.65 against $98.87.

Noticed by:
Included it: Grok, Nova, DeepSeek, MiMo. Did not include: ChatGPT, Meta, Gemini, Wenxin.
Source ↗

cubic's bug rates moved between publications (Opus 5.5 from 1.49 to 1.14, GPT-6.1 Sol from 1.22 to 0.76). The windows changed; this is not proof the models improved. A third reading (GPT-6 Luna 0.47) appears in only one answer and is not confirmed.

Noticed by:
Included it: ChatGPT, Grok, DeepSeek. Did not include: Meta, Gemini, Nova, Wenxin, MiMo.
Source ↗

04Questions people ask

what is the best model for coding 2026

It depends on the seat. GPT-6.1 Sol has the lowest counted bug rate at 0.76, Claude Opus 5.5 leads Terminal-Bench 4.0 at 64.8%, and GPT-6 Astra leads FrontierSWE v2 at 65.5%.

Source ↗
gpt vs claude for coding

GPT-6 Astra beats Opus 5.5 on 20-hour tasks, 65.5% to 62.3%. Opus 5.5 beats Astra on terminal tasks in their own harnesses, 64.8% to 58.2%.

Source ↗
gpt 5 vs claude for coding

GPT-5.6 Sol had a 0.62 bug rate inside Codex in October, but scores 32.2% on FrontierSWE v2 against Opus 5.5's 62.3% in the same harness.

Source ↗
why do coding model bug rates differ between sources

cubic's Oct 16 article measured short windows inside each agent, while its Nov 4 board pools Jul 13 to Nov 1. That is why Opus 5.5 shows 1.49 in one and 1.14 in the other.

Source ↗

05How we counted

In plain words, no formulas.

1The question

Top 10 models to seat on one coding-agent team

2Why this topic

The reader gets a model-by-seat choice that no single leaderboard gives, and it answers a question people search all year.

3Where it applies

global, people who pick the model inside Claude Code, Codex, Cursor or a similar agent

4What we looked at

  • Counted bugs per line in code real teams shipped through that agent
  • Share of terminal tasks solved in the vendor's own harness
  • Score on day-long tasks when the harness is the same for every model
  • List price of output tokens set against the bug rate
  • cubic Bug Bench — Counted bugs per AI-attributed line against the average (1.00; lower is cleaner). The Nov 4 ranking covers Jul 13 to Nov 1. The Oct 16 article used shorter, agent-specific windows. O
  • Terminal-Bench 4.0 (tbench.ai) — Resolution rate on 66 terminal tasks with the vendor's own harness named.
  • Proximal FrontierSWE v2 — Mean@5 score on 34 tasks of up to 20 hours, with every model in one shared Proximus harness.
  • cubic list price vs bug rate — Provider list price per million output tokens, set next to the relative bug rate.

5Who ranked

The leading AIs, each building its own list of ten independently and naming a source for every place: ChatGPT, Meta, Grok, Gemini, Nova, DeepSeek, Wenxin, MiMo.

6How the places were set

The same entry written differently by different AIs was counted as one. The more AIs put an entry on their list, and the higher they put it, the higher its place. "AI agreement" shows how many of the AIs had it on their own list. Sources are only those the AIs found themselves; nothing was added by hand.

06Each AI's own list

🇺🇸 ChatGPT10 places · 3 notes

The same question, answered by ChatGPT alone. The final list above combines all the AIs.

  1. 1
    GPT-6.1 Sol (2026)

    A 0.76 relative bug rate and the same 58.2% terminal result as Astra, at one-fifth Astra's standard output-token price.

    Source ↗
  2. 2
    Claude Opus 5.5 (2026)

    The terminal-task leader at 64.8%, yet its 1.14 pooled bug rate is worse than the average in cubic's reviewed code.

    Source ↗
  3. 3
    GPT-6 Astra (2026)

    The 20-hour engineering champion at 65.5%, but its $50 output-token price makes it an escalation model rather than my everyday default.

    Source ↗
  4. 4
    Claude Sonnet 5.5 (2026)

    61.8% terminal resolution puts it within three points of Opus 5.5, making it a serious implementation seat.

    Source ↗
  5. 5
    Claude Fable 5.1 (2026)

    Its 0.93 pooled bug rate beats Opus 5.5's 1.14, despite Opus being far more widely used.

    Source ↗
  6. 6
    Gemini 4 Carbon (2026)

    61.2% on FrontierSWE v2 puts it just 1.1 points behind Opus 5.5 under the same harness.

  7. 7
    GPT-5.6 Sol (2026)

    Its historical 0.62 Codex bug rate was excellent, but a 32.2% long-horizon score argues against giving it the hardest seat.

    Source ↗
  8. 8
    Claude Opus 5 (2026)

    A 1.21 pooled bug rate leaves it behind the newer Opus 5.5, without a clear statistical improvement established across the family.

    Source ↗
  9. 9
    Claude Opus 4.8 (2026)

    Its share fell from 29.4% in July to 0.5% in late October, illustrating how quickly coding-model defaults change.

    Source ↗
  10. 10
    Grok 4.7 (2026)

    A 1.79 relative bug rate makes it the least convincing default implementation seat among cubic's eight currently ranked models.

    Source ↗

What ChatGPT noticed

The most-used model is not the cleanest in reviewed code: Opus 5.5 wrote 64.4% of cubic's AI-attributed lines in the latest complete week, but GPT-6.1 Sol had the lowest relative bug rate, 0.76 versus 1.14.

Astra and Sol both reached 58.2% in Terminal-Bench 4.0 using Codex, yet their estimated API task costs were $9.90 and $1.92 respectively. Identical rounded resolution rates do not establish identical performance on every task.

Output-token list price is not task cost. A model using fewer tokens or finishing faster can cost less per solved task even when its price per million output tokens is higher.

🇺🇸 Meta10 places · 4 notes

The same question, answered by Meta alone. The final list above combines all the AIs.

  1. 1
    GPT-5.6 Sol 2026

    0.62 inside Codex, 0.65 overall — only model below average, 35% fewer bugs, but 0.7% of reviewed code Oct 5 week

    Source ↗
  2. 2
    Claude Fable 5.1 2026

    1.09 inside Claude Code cleanest there, 56.3% FrontierSWE, tied with Sonnet 5.5 but costs 5× more

    Source ↗
  3. 3
    GPT-6 Astra 2026

    65.5% FrontierSWE v2 leader + 58.2% Terminal-Bench, yet 1.13 bug rate above average — the 20-hour survivor

  4. 4
    Claude Opus 5.5 2026

    64.8% Terminal-Bench #1, 62.3% FrontierSWE #2, but 1.49 bug rate worst inside Claude Code — strong terminal, dirty everyday

    Source ↗
  5. 5
    Claude Sonnet 5.5 2026

    61.8% Terminal-Bench, 61.9% FrontierSWE, 1.24 bug rate tied with Fable inside Claude Code at one-fifth price

    Source ↗
  6. 6
    GPT-6.1 Sol 2026

    58.2% Terminal-Bench tie with Astra for $1.92 vs $14.30, 1.22 bug rate inside Codex, OpenAI recommended for complex coding

    Source ↗
  7. 7
    Gemini 4 Carbon 2026

    61.2% FrontierSWE v2 rank 4, no Bug Bench rate — best non-OpenAI/Anthropic long-horizon score

  8. 8
    Claude Opus 5 2026

    52.0% FrontierSWE, 1.33 bug rate, 51.8% Terminal-Bench old — superseded by Opus 5.5 at 20% lower price

    Source ↗
  9. 9
    Gemini 4 Argon 2026

    55.0% FrontierSWE, no Bug Bench, breadth leader per Google comparison table Oct 2026

  10. 10
    Claude Haiku 5.5 2026

    43.8% FrontierSWE, unranked in Bug Bench Oct 5 window, $0.50 output — cheapest Claude for routine seat

    Source ↗

What Meta noticed

Vendor default is not cleanest: Claude Code defaults to Opus 5.5 at 1.49 bug rate worst in agent, while Fable 5.1 at 1.09 is cleanest inside Claude Code; Codex recommends 6.1 Sol 1.22 while 5.6 Sol 0.62 is cleanest

Clean everyday vs terminal vs 20-hour are three seats: GPT-5.6 Sol wins bugs 0.62, Opus 5.5 wins terminal 64.8%, Astra wins 20h 65.5% — no model wins all three

Price per clean line flips ranking: Sol $10 output at 0.65 vs Astra $50 at 1.13 — Astra costs 5× for 13% more bugs than average

GPT-5.6 Sol wrote 35% of AI code Aug 17 week but 0.7% Oct 5 week — cleanest model is now rarest in reviewed data

🇺🇸 Grok10 places · 4 notes

The same question, answered by Grok alone. The final list above combines all the AIs.

  1. 1
    GPT-6.1 Sol

    The fewest counted bugs of any ranked model, at 0.76, and the same 58.2% terminal score as Astra at about $634 for the Codex run instead of $3.3k.

    Source ↗
  2. 2
    Claude Sonnet 5.5

    At $10 per million output tokens it sits near the terminal leader, 61.8% in Claude Code, and near the day-long leader, 61.9% in the shared harness.

    Source ↗
  3. 3
    Claude Opus 5.5

    It wrote 64.4% of the AI code cubic reviewed in the week of Oct 26, and it is not the clean model in Claude Code: 1.13 now, 1.49 in the October writeup.

    Source ↗
  4. 4
    GPT-6 Astra

    It leads the 20-hour board at 65.5%, at about $1,030 a trial, and on terminal tasks it does not beat the $10-output Sol model.

    Source ↗
  5. 5
    Claude Fable 5.1

    The cleanest model inside Claude Code, at 0.93, while the default people actually run is Opus 5.5.

    Source ↗
  6. 6
    Gemini 4 Carbon

    Fourth on the shared 20-hour board at 61.2%, and cubic has no counted bug rate for it.

  7. 7
    GLM-5.3

    The open-weight seat: 41.8% of terminal tasks inside Claude Code, and 30.2% on the 20-hour board.

    Source ↗
  8. 8
    Claude Opus 5

    Inside Cursor it is the least-buggy ranked model, at 1.22, which is still 22% more counted bugs than average.

    Source ↗
  9. 9
    GPT-5.6 Sol

    It was the cleanest model inside Codex at 0.62, and on day-long tasks it scores 32.2%, about half of Astra.

    Source ↗
  10. 10
    Grok 4.7

    The cheapest ranked output token, at $6 per million, comes with the highest ranked bug rate, 1.79.

    Source ↗

What Grok noticed

Claude Code's default on paid plans is Opus 5.5. Inside that agent the lowest bug rate on the Nov 4 window is Fable 5.1 at 0.93, tied with Sonnet 5.5 at 1.00, while Opus 5.5 is at 1.13.

GPT-6 Astra and GPT-6.1 Sol resolve the same 58.2% of Terminal-Bench 4.0 inside Codex. Astra's listed run is about $3.3k and Sol's is about $634.

On FrontierSWE v2, Astra at 65.5% costs about 10 times a trial what Opus 5.5 costs at 62.3%: about $1,029.65 against $98.87.

GPT-5.6 Sol led Codex on counted bugs at 0.62 in cubic's October article, then fell under 0.5% of AI-attributed lines and left the Nov 4 ranking. Its day-long score is 32.2%.

🇺🇸 Gemini10 places

The same question, answered by Gemini alone. The final list above combines all the AIs.

  1. 1
    GPT-6 Astra

    Dominates 20-hour marathon tasks at 65.5% on FrontierSWE v2 while maintaining a 58.2% CLI resolution rate inside Codex.

  2. 2
    Claude Opus 5.5

    The reigning command-line benchmark leader at 64.8% on Terminal-Bench 4.0 and 62.3% on FrontierSWE v2, though carrying a 1.49 relative defect rate.

  3. 3
    GPT-5.6 Sol

    The cleanest production coder recorded: an exceptionally low 0.62 relative bug rate, making it the most reliable everyday workhorse despite a modest 32.2% 20-hour task score.

  4. 4
    Claude Sonnet 5.5

    Delivers 61.8% on Terminal-Bench 4.0 at a fraction of Opus output pricing, serving as the industry standard daily driver for agentic CLI loops.

  5. 5
    Claude Fable 5.1

    Combines a solid 57.9% Terminal-Bench 4.0 completion rate with a 1.09 relative bug rate, significantly cleaner in review than Opus 5.5.

  6. 6
    GPT-6.1 Sol

    Matches Astra's 58.2% CLI resolution inside Codex with higher iterative reasoning depth, registering a 1.22 relative bug rate.

  7. 7
    Grok 4.7

    Achieves 37.6% on Terminal-Bench 4.0 inside Grok Build, providing high token throughput for systems diagnostics and infrastructure automation.

  8. 8
    Gemini 2.5 Pro

    Leverages a 2-million-token native context window to ingest entire multi-repo codebases in a single prompt for complex cross-dependency migration.

    Source ↗
  9. 9
    DeepSeek V3.5 Coder

    Open-weights cost leader that drastically undercuts commercial token pricing for high-frequency unit-test generation and automated PR linting swarms.

  10. 10
    Qwen 2.5 Coder 32B

    The premier self-hosted model for on-premises enterprise codebases where zero cloud data leakage and air-gapped compliance are non-negotiable.

    Source ↗
🇨🇳 DeepSeek10 places · 3 notes

The same question, answered by DeepSeek alone. The final list above combines all the AIs.

  1. 1
    GPT-6.1 Sol

    0.98 relative bug rate and 58.2% on Terminal-Bench for $10 output — the best all-round seat, a hair behind Astra on long-horizon work but five times cheaper.

    Source ↗
  2. 2
    Claude Sonnet 5.5

    1.06 bug rate and 61.8% Terminal-Bench for $10 output: the cheapest way to get Claude Code's top-tier terminal score.

    Source ↗
  3. 3
    GPT-6 Astra

    65.5% FrontierSWE and 58.2% Terminal-Bench: the best day-long-task model on the board, but $50 output and a 1.09 bug rate.

    Source ↗
  4. 4
    GPT-6 Luna

    0.47 bug rate — 53% fewer counted bugs than average — for $0.50 output, but it scores only 16.4% on Terminal-Bench, so it's a clean everyday seat, not a closer.

    Source ↗
  5. 5
    Claude Opus 5.5

    64.8% Terminal-Bench and 62.3% FrontierSWE: the strongest Claude Code pairing for hard work, but its 1.39 bug rate is the worst on Bug Bench.

    Source ↗
  6. 6
    Kimi K3.1 Pro

    67.2% Terminal-Bench (Artificial Analysis) at $10 output: the raw terminal champion, but 25.9% FrontierSWE and no Bug Bench rank make it a specialist.

  7. 7
    Claude Fable 5.1

    1.07 bug rate, 57.9% Terminal-Bench and 56.3% FrontierSWE — balanced, but at $50 output it costs the same as Astra without Astra's long-horizon lead.

    Source ↗
  8. 8
    Gemini 4 Argon

    55.0% FrontierSWE and 57.6% Terminal-Bench at an introductory $10 output — a credible third seat, though its bug density drew independent criticism.

    Source ↗
  9. 9
    GPT-5.6 Sol

    0.62 bug rate inside Codex — 38% fewer counted bugs than average — but 37.3% Terminal-Bench and 32.2% FrontierSWE: the cleanest small-task seat, not a long-hauler.

    Source ↗
  10. 10
    Claude Opus 5

    1.30 bug rate, 53.9% Terminal-Bench, 52.0% FrontierSWE and $25 output — a middle seat that's neither the cleanest nor the strongest anymore.

    Source ↗

What DeepSeek noticed

The cheapest model wins the bug bench: GPT-6 Luna at $0.50 output has the lowest relative bug rate (0.47) — 53% below average — while the $50 Fable 5.1 and Astra sit at 1.07 and 1.09.

Opus 5.5 is the most contradictory seat: best Claude Code Terminal-Bench score (64.8%) and second on FrontierSWE (62.3%), but worst Bug Bench rate (1.39).

Price per trial flips the FrontierSWE list: GPT-6 Astra leads at 65.5% but costs $1,029.65 per trial; Opus 5.5 costs $98.87, 90% less, for 3.2 fewer points.

🇨🇳 Wenxin10 places · 2 notes

The same question, answered by Wenxin alone. The final list above combines all the AIs.

  1. 1
    GPT-5.6 Sol (OpenAI, inside Codex) 2026

    Lowest observed bug rate (0.62) at Codex pricing — clean code for the price of a latte per 1 M tokens.

    Source ↗
  2. 2
    GPT-6 Astra (OpenAI, inside Codex) 2026

    FrontierSWE champion 65.5 % and 58.2 % on terminals — but 1.13 bugs/line makes it pricier per clean line.

  3. 3
    Claude Opus 5.5 (Anthropic, inside Claude Code) 2026

    64.8 % on terminals, 62.3 % on 20-h tasks — but 1.49 bugs/line puts it behind on cleanliness.

    Source ↗
  4. 4
    Claude Sonnet 5.5 (Anthropic, inside Claude Code) 2026

    61.8 % terminals at likely half the price of Opus — the workhorse pick.

    Source ↗
  5. 5
    Claude Fable 5.1 (Anthropic, inside Claude Code) 2026

    57.9 % on terminals, 1.09 bugs/line — mid-tier clean, mid-tier price, sweet spot for daily coding.

    Source ↗
  6. 6
    GPT-6.1 Sol (OpenAI, inside Codex) 2026

    58.2 % terminals and 1.22 bugs/line — faster than Astra, slightly cleaner, same price tier.

  7. 7
    Grok 4.7 (xAI, inside Grok Build) 2026

    37.6 % on terminals — the frontier terminal model is not the frontier long-task model.

    Source ↗
  8. 8
    DeepSeek-V3 (DeepSeek, via API) 2026

    Open-weight, sub-2/1M tokens; bug rate not in cubic top list but community reports ~1.3.

  9. 9
    Qwen 3 (Alibaba, via API) 2026

    Open-weight, strong on terminals in Chinese-language benchmarks; English cubic data thin.

  10. 10
    Gemini 2.5 Pro (Google, via Vertex/AI Studio) 2026

    Google's 2026 flagship; cubic and terminal data not yet in top tables but long-context strong.

    Source ↗

What Wenxin noticed

Claude Fable 5.1 costs roughly one-fifteenth of Claude Opus 5.5 per token yet delivers 57.9 % on terminals and only 1.09 bugs/line — the price-performance champion for daily agentic coding.

GPT-6 Astra leads FrontierSWE (65.5 %) but its 1.13 bug rate means a team shipping 100 K lines a month pays ~1.4 M in tokens for the same clean output that Fable delivers for ~0.07 M.

🇨🇳 MiMo10 places · 4 notes

The same question, answered by MiMo alone. The final list above combines all the AIs.

  1. 1
    Claude Opus 5.5 (Anthropic, 2026)

    Wins the terminal board in its harness at 64.8% and survives 20-hour tasks at 62.3% — for about $99 a trial where the winner of that board pays $1,030.

    Source ↗
  2. 2
    GPT-6 Astra (OpenAI, 2026)

    The only model that finished the 20-hour tasks in first place — at $1,029.65 per trial and 1.13 counted bugs per line in Codex.

    Source ↗
  3. 3
    GPT-5.6 Sol (OpenAI, 2026)

    The cleanest code on the board — 0.62 bugs per line inside Codex — and the weakest long-task score of the top models at 32.2%.

    Source ↗
  4. 4
    Claude Sonnet 5.5 (Anthropic, 2026)

    Within about two points of Opus 5.5 in coding sessions at a lower tier — the value seat of the Anthropic pair.

    Source ↗
  5. 5
    GPT-6.1 Sol (OpenAI, 2026)

    Same terminal score as the flagships (58.2%) at $10 per million output tokens — five times cheaper than Astra, but 1.22 bugs per line.

    Source ↗
  6. 6
    Claude Fable 5.1 (Anthropic, 2026)

    The everyday specialist: 57.9% on terminal tasks and the cleanest code measured inside Claude Code at 1.09.

    Source ↗
  7. 7
    GPT-6.1 Terra (OpenAI, 2026)

    OpenAI says it matches Astra at one-tenth the token price and burns tokens three times more efficiently than Opus 5.5.

    Source ↗
  8. 8
    Gemini 4 Argon (Google, 2026)

    A full FrontierSWE trial costs $129.36 — about one-eighth of Astra's — so it is the budget seat for day-long tasks.

    Source ↗
  9. 9
    Claude Opus 5 (Anthropic, 2025)

    The previous generation still finishes half the 20-hour tasks (52.0%) where newer cheaper models stall at 32%.

    Source ↗
  10. 10
    Grok 4.7 (xAI, 2026)

    The third place worth a seat on a mixed team: 37.6% of terminal tasks in its own harness — real, but a full tier below the leaders.

    Source ↗

What MiMo noticed

The cleanest model and the strongest model are not the same seat: inside Codex, GPT-5.6 Sol counts 0.62 bugs per line versus GPT-6 Astra's 1.13 — yet Astra alone wins the 20-hour tasks.

Winning FrontierSWE v2 costs GPT-6 Astra $1,029.65 per trial; Claude Opus 5.5 reaches 62.3% for $98.87 — a 3.2-point gap for ten times the money.

Inside Claude Code the vendor's own flagship is the dirtier writer: Opus 5.5 1.49 bugs per line versus Fable 5.1's 1.09.

The biggest ranking jump of the year is generational, not vendor: Opus 4.8 solved 23.6% of terminal tasks, Opus 5.5 solves 64.8%.