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Model A
Gemini 3.6 Flash

Google

70.11/100

Supported · Public rank #21

90% interval 63.775.9

Gemini 3.6 Flash vs GPT-5.1-Codex-Max

Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

OpenAI logo
Model B
GPT-5.1-Codex-Max

OpenAI

53.96/100

Estimated · Public rank #113

90% interval 42.465.5

Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.

0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Long documents

    Prompts that approach the documented context limit

    Gemini 3.6 Flash

    Gemini 3.6 Flash has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Gemini 3.6 Flash

    Gemini 3.6 Flash has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Gemini 3.6 Flash

    Gemini 3.6 Flash has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

Show secondary and unsupported calls
  • Repository review cost

    50K fresh input + 3K output tokens

    GPT-5.1-Codex-Max

    GPT-5.1-Codex-Max has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    GPT-5.1-Codex-Max is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    GPT-5.1-Codex-Max is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
0
Gemini 3.6 Flash only
8
GPT-5.1-Codex-Max only
1
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Not comparable
Gemini 3.6 Flash
50.7
Supported · #60/151
GPT-5.1-Codex-Max
Not ranked
Basis
BenchAlign lane · 2 vs 0 public rows
Reading
Not comparable

Coding

Not comparable
Gemini 3.6 Flash
58.9
Supported · #30/183
GPT-5.1-Codex-Max
Not ranked
Basis
BenchAlign lane · 4 vs 1 public rows
Reading
Not comparable

Reasoning

Not comparable
Gemini 3.6 Flash
77.8
Unranked · 2 rankable rows
GPT-5.1-Codex-Max
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Gemini 3.6 Flash
68.6
Supported · #18/181
GPT-5.1-Codex-Max
Not ranked
Basis
BenchAlign lane · 2 vs 0 public rows
Reading
Not comparable

Math

Not comparable
Gemini 3.6 Flash
Not ranked
GPT-5.1-Codex-Max
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.6 Flash
Not ranked
GPT-5.1-Codex-Max
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3.6 Flash
82.3
Unranked · 1 rankable row
GPT-5.1-Codex-Max
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.6 Flash
Not ranked
GPT-5.1-Codex-Max
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Gemini 3.6 Flash
$0.00525
Fits in one request
GPT-5.1-Codex-Max
$0.00625
Fits in one request

Gemini 3.6 Flash has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Gemini 3.6 Flash
$0.0975
Fits in one request
GPT-5.1-Codex-Max
$0.0925
Fits in one request

GPT-5.1-Codex-Max has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Gemini 3.6 Flash
$0.135
Fits in one request
GPT-5.1-Codex-Max
$0.15
Fits in one request

Gemini 3.6 Flash has the lower modeled cost

Costs use the listed standard API rates.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Reasoning profile

Gemini 3.6 Flash

Reasoning

GPT-5.1-Codex-Max

Reasoning

Weight access

Gemini 3.6 Flash

Proprietary

GPT-5.1-Codex-Max

Proprietary

License

Gemini 3.6 Flash

Proprietary

GPT-5.1-Codex-Max

Proprietary

Release date

Gemini 3.6 Flash

2026-07-21

GPT-5.1-Codex-Max

2025-11-19

If you already use one of these models
Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
Repository review: $0.0975 vs $0.0925. Cache-heavy agent loop: $0.135 vs $0.15.
Context tradeoff
Gemini 3.6 Flash has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence9 rows

Agentic

  • OSWorld-Verified

    Gemini 3.6 Flash83%
    Source
    GPT-5.1-Codex-Max

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.6 Flash73.8%
    Source
    GPT-5.1-Codex-Max

    Not directly comparable

Coding

  • deepSwe

    Gemini 3.6 Flash49%
    Source
    GPT-5.1-Codex-Max

    Not directly comparable

  • cursorBench32

    Gemini 3.6 Flash53.5%
    Source
    GPT-5.1-Codex-Max

    Not directly comparable

  • LiveCodeBench (Vals)

    Gemini 3.6 Flash88.1%
    Source
    GPT-5.1-Codex-Max

    Not directly comparable

  • SWE-bench (Vals)

    Gemini 3.6 Flash79.6%
    Source
    GPT-5.1-Codex-Max

    Not directly comparable

  • Vibe Code Bench

    Gemini 3.6 Flash
    GPT-5.1-Codex-Max22.17%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Gemini 3.6 Flash93.4%
    Source
    GPT-5.1-Codex-Max

    Not directly comparable

  • MMLU-Pro (Vals)

    Gemini 3.6 Flash89.3%
    Source
    GPT-5.1-Codex-Max

    Not directly comparable

Frequently asked questions

Which is better, Gemini 3.6 Flash or GPT-5.1-Codex-Max?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Gemini 3.6 Flash or GPT-5.1-Codex-Max?

GPT-5.1-Codex-Max is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Gemini 3.6 Flash or GPT-5.1-Codex-Max?

GPT-5.1-Codex-Max is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Gemini 3.6 Flash or GPT-5.1-Codex-Max?

For the stated presets, chat costs $0.00525 on Gemini 3.6 Flash and $0.00625 on GPT-5.1-Codex-Max; repository review costs $0.0975 and $0.0925; the cache-heavy agent loop costs $0.135 and $0.15. Costs use the listed standard API rates.

Which has the larger context window, Gemini 3.6 Flash or GPT-5.1-Codex-Max?

Gemini 3.6 Flash has the larger documented context window: 1M, compared with 400K.

Related comparisons

Last updated September 4, 2026

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