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Model comparison

GPT-5.5 Pro vs Qwen 3.6 Max (preview)

Updated July 29, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

GPT-5.5 Pro

OpenAI

62.8/100

Estimated · Public rank #42

90% interval 47.8–77.8

Qwen 3.6 Max (preview)

Alibaba

59.3/100

Supported · Public rank #56

90% interval 40.4–78.2

GPT-5.5 Pro has the higher public score estimate, 62.79 versus 59.29, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

2 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

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

    GPT-5.5 Pro

    GPT-5.5 Pro has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

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

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: rate-fallback

  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

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
2
GPT-5.5 Pro only
4
Qwen 3.6 Max (preview) only
7
Like-for-like categories
1 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Math

Like-for-like
GPT-5.5 Pro
48.1
Qwen 3.6 Max (preview)
18.4
Weighted basis
2 vs 2 rows
Reading
GPT-5.5 Pro leads

Agentic

Not comparable
GPT-5.5 Pro
90.1
Qwen 3.6 Max (preview)
65.4
Weighted basis
1 vs 1 rows
Reading
Not comparable

Coding

Not comparable
GPT-5.5 Pro
Not measured
Qwen 3.6 Max (preview)
51.0
Weighted basis
0 vs 2 rows
Reading
Not comparable

Reasoning

Not comparable
GPT-5.5 Pro
Not measured
Qwen 3.6 Max (preview)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
GPT-5.5 Pro
57.2
Qwen 3.6 Max (preview)
73.9
Weighted basis
1 vs 1 rows
Reading
Not comparable

Multilingual

Not comparable
GPT-5.5 Pro
Not measured
Qwen 3.6 Max (preview)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
GPT-5.5 Pro
Not measured
Qwen 3.6 Max (preview)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
GPT-5.5 Pro
Not measured
Qwen 3.6 Max (preview)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

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.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

  • FrontierMath v2 (Tier 4)

    Math

    GPT-5.5 Pro: 39.600%Qwen 3.6 Max (preview): 4.167%Normalized gap 35.4Shared source
  • FrontierMath v2 (Tiers 1-3)

    Math

    GPT-5.5 Pro: 51.000%Qwen 3.6 Max (preview): 23.103%Normalized gap 27.9Shared source

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

GPT-5.5 Pro
$0.12
Fits in one request
Qwen 3.6 Max (preview)
API rate not published
Fits in one request

Qwen 3.6 Max (preview) has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

GPT-5.5 Pro
$2.04
Fits in one request
Qwen 3.6 Max (preview)
API rate not published
Fits in one request

Qwen 3.6 Max (preview) has no comparable published API token rate.

Cache-heavy agent loop

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

GPT-5.5 Pro
$8.40
Fits in one request
Cached input priced at the published list-input rate
Qwen 3.6 Max (preview)
API rate not published
Fits in one request
Cached-input rate unavailable

GPT-5.5 Pro has no published cached-input rate, so cached tokens use its listed input rate. Qwen 3.6 Max (preview) has no comparable published API token rate.

Specification differences

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

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

GPT-5.5 Pro

Not published

OpenAI pricing

Qwen 3.6 Max (preview)

No comparable hosted API rate

Provider availability

GPT-5.5 Pro

Generally Available · OpenAI Responses API

OpenAI model catalog

Qwen 3.6 Max (preview)

Not sourced

Reasoning profile

GPT-5.5 Pro

Reasoning

Qwen 3.6 Max (preview)

Reasoning

Weight access

GPT-5.5 Pro

Proprietary

Qwen 3.6 Max (preview)

Proprietary

License

GPT-5.5 Pro

Proprietary

Qwen 3.6 Max (preview)

Proprietary

Release date

GPT-5.5 Pro

2026-04-23

Qwen 3.6 Max (preview)

2026-04-20

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
GPT-5.5 Pro has the higher public score estimate, 62.79 versus 59.29, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
GPT-5.5 Pro has the larger documented window (1.05M).

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 evidence13 rows

Agentic

  • BrowseComp

    GPT-5.5 Pro90.1%
    Source
    Qwen 3.6 Max (preview)

    Not directly comparable

  • Terminal-Bench 2.0

    GPT-5.5 Pro
    Qwen 3.6 Max (preview)65.4%
    Source

    Not directly comparable

  • QwenClawBench

    GPT-5.5 Pro
    Qwen 3.6 Max (preview)59.0%
    Source

    Not directly comparable

Coding

  • SWE-bench Pro

    GPT-5.5 Pro
    Qwen 3.6 Max (preview)57.3%
    Source

    Not directly comparable

  • SciCode

    GPT-5.5 Pro
    Qwen 3.6 Max (preview)47%
    Source

    Not directly comparable

  • NL2Repo

    GPT-5.5 Pro
    Qwen 3.6 Max (preview)42.9%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    GPT-5.5 Pro
    Qwen 3.6 Max (preview)65.4%
    Source

    Not directly comparable

Knowledge

  • HLE

    GPT-5.5 Pro57.2%
    Source
    Qwen 3.6 Max (preview)

    Not directly comparable

  • HLE w/o tools

    GPT-5.5 Pro43.1%
    Source
    Qwen 3.6 Max (preview)

    Not directly comparable

  • SuperGPQA

    GPT-5.5 Pro
    Qwen 3.6 Max (preview)73.9%
    Source

    Not directly comparable

Math

  • FrontierMath (legacy)

    GPT-5.5 Pro52.4%
    Source
    Qwen 3.6 Max (preview)

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Shared source
    GPT-5.5 Pro51.000%
    Qwen 3.6 Max (preview)23.103%

    GPT-5.5 Pro leads this result

  • FrontierMath v2 (Tier 4)

    Shared source
    GPT-5.5 Pro39.600%
    Qwen 3.6 Max (preview)4.167%

    GPT-5.5 Pro leads this result

Frequently asked questions

Which is better, GPT-5.5 Pro or Qwen 3.6 Max (preview)?

GPT-5.5 Pro has the higher public score estimate, 62.79 versus 59.29, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, GPT-5.5 Pro or Qwen 3.6 Max (preview)?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, GPT-5.5 Pro or Qwen 3.6 Max (preview)?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, GPT-5.5 Pro or Qwen 3.6 Max (preview)?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, GPT-5.5 Pro or Qwen 3.6 Max (preview)?

GPT-5.5 Pro has the larger documented context window: 1.05M, compared with 256K.

Related comparisons

Last updated July 29, 2026

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