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Model comparison

Mistral Medium 3 vs Qwen3.5 397B

Updated July 31, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Mistral Medium 3

Mistral

—

Evidence status unavailable

90% interval unavailable

Qwen3.5 397B

Alibaba

56.2/100

Estimated · Public rank #79

90% interval 44.7–67.7

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 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.

  • Chat turn cost

    1K fresh input + 500 output tokens

    Mistral Medium 3

    Mistral Medium 3 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

    Mistral Medium 3

    Mistral Medium 3 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

    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

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

  • Cache-heavy agent loop cost

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

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Mistral Medium 3 does not fit this workload in one request. Qwen3.5 397B does not fit this workload in one request. Mistral Medium 3 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

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
Mistral Medium 3 only
0
Qwen3.5 397B only
38
Like-for-like categories
0 / 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.

Agentic

Not comparable
Mistral Medium 3
Not measured
Qwen3.5 397B
56.5
Weighted basis
0 vs 2 rows
Reading
Not comparable

Coding

Not comparable
Mistral Medium 3
Not measured
Qwen3.5 397B
66.5
Weighted basis
0 vs 2 rows
Reading
Not comparable

Reasoning

Not comparable
Mistral Medium 3
Not measured
Qwen3.5 397B
63.2
Weighted basis
0 vs 1 rows
Reading
Not comparable

Knowledge

Not comparable
Mistral Medium 3
Not measured
Qwen3.5 397B
56.6
Weighted basis
0 vs 4 rows
Reading
Not comparable

Math

Not comparable
Mistral Medium 3
Not measured
Qwen3.5 397B
90.6
Weighted basis
0 vs 2 rows
Reading
Not comparable

Multilingual

Not comparable
Mistral Medium 3
Not measured
Qwen3.5 397B
84.7
Weighted basis
0 vs 1 rows
Reading
Not comparable

Multimodal

Not comparable
Mistral Medium 3
Not measured
Qwen3.5 397B
79.6
Weighted basis
0 vs 2 rows
Reading
Not comparable

Instruction following

Not comparable
Mistral Medium 3
Not measured
Qwen3.5 397B
92.6
Weighted basis
0 vs 1 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.

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

Mistral Medium 3
$0.0014
Fits in one request
Qwen3.5 397B
$0.0024
Fits in one request

Mistral Medium 3 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Mistral Medium 3
$0.026
Fits in one request
Qwen3.5 397B
$0.0408
Fits in one request

Mistral Medium 3 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Mistral Medium 3
$0.108
Does not fit in one request
Cached input priced at the published list-input rate
Qwen3.5 397B
$0.168
Does not fit in one request
Cached input priced at the published list-input rate

Mistral Medium 3 does not fit this workload in one request. Qwen3.5 397B does not fit this workload in one request. Mistral Medium 3 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate.

Specification differences

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

Context window

Maximum documented context; output-token limits may be lower.

Mistral Medium 3

128K

Qwen3.5 397B

128K

API model ID

Mistral Medium 3

Not sourced

Qwen3.5 397B

Not sourced

Cached-input rate

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

Mistral Medium 3

Not published

Qwen3.5 397B

Not published

Documented inputs

Mistral Medium 3

Not sourced

Qwen3.5 397B

Not sourced

Documented outputs

Mistral Medium 3

Not sourced

Qwen3.5 397B

Not sourced

Provider availability

Mistral Medium 3

Not sourced

Qwen3.5 397B

Not sourced

Reasoning profile

Mistral Medium 3

Non-Reasoning

Qwen3.5 397B

Non-Reasoning

Weight access

Mistral Medium 3

Proprietary

Qwen3.5 397B

Open Weight

License

Mistral Medium 3

Proprietary

Qwen3.5 397B

Open Weight

Release date

Mistral Medium 3

2026-02-20

Qwen3.5 397B

2026-02-16

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: $0.026 vs $0.0408. Cache-heavy agent loop: $0.108 vs $0.168.
Context tradeoff
Both models list 128K.

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 evidence38 rows

Agentic

  • Terminal-Bench 2.0

    Mistral Medium 3—
    Qwen3.5 397B52.5%
    Source

    Not directly comparable

  • BrowseComp

    Mistral Medium 3—
    Qwen3.5 397B62%
    Source

    Not directly comparable

  • Claw-Eval

    Mistral Medium 3—
    Qwen3.5 397B56.8%
    Source

    Not directly comparable

  • QwenClawBench

    Mistral Medium 3—
    Qwen3.5 397B51.8%
    Source

    Not directly comparable

  • τ³-bench results

    Mistral Medium 3—
    Qwen3.5 397B68.4%
    Source

    Not directly comparable

  • VITA-Bench

    Mistral Medium 3—
    Qwen3.5 397B43.7%
    Source

    Not directly comparable

  • DeepPlanning

    Mistral Medium 3—
    Qwen3.5 397B37.6%
    Source

    Not directly comparable

  • Toolathlon

    Mistral Medium 3—
    Qwen3.5 397B36.3%
    Source

    Not directly comparable

  • MCP Atlas

    Mistral Medium 3—
    Qwen3.5 397B46.1%
    Source

    Not directly comparable

  • MCP-Tasks

    Mistral Medium 3—
    Qwen3.5 397B74.2%
    Source

    Not directly comparable

  • WideResearch

    Mistral Medium 3—
    Qwen3.5 397B74.0%
    Source

    Not directly comparable

  • Gert Labs

    Mistral Medium 3—
    Qwen3.5 397B46.76%
    Source

    Not directly comparable

  • ResearchClawBench

    Mistral Medium 3—
    Qwen3.5 397B14.2%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Mistral Medium 3—
    Qwen3.5 397B76.2%
    Source

    Not directly comparable

  • LiveCodeBench v6

    Mistral Medium 3—
    Qwen3.5 397B83.6%
    Source

    Not directly comparable

  • SWE-bench Pro

    Mistral Medium 3—
    Qwen3.5 397B50.9%
    Source

    Not directly comparable

Reasoning

  • LongBench v2

    Mistral Medium 3—
    Qwen3.5 397B63.2%
    Source

    Not directly comparable

  • AI-Needle

    Mistral Medium 3—
    Qwen3.5 397B68.7%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Mistral Medium 3—
    Qwen3.5 397B88.4%
    Source

    Not directly comparable

  • SuperGPQA

    Mistral Medium 3—
    Qwen3.5 397B70.4%
    Source

    Not directly comparable

  • MMLU-Pro

    Mistral Medium 3—
    Qwen3.5 397B87.8%
    Source

    Not directly comparable

  • MMLU-Redux

    Mistral Medium 3—
    Qwen3.5 397B94.9%
    Source

    Not directly comparable

  • C-Eval

    Mistral Medium 3—
    Qwen3.5 397B93%
    Source

    Not directly comparable

  • HLE

    Mistral Medium 3—
    Qwen3.5 397B28.7%
    Source

    Not directly comparable

Math

  • AIME26

    Mistral Medium 3—
    Qwen3.5 397B93.3%
    Source

    Not directly comparable

  • HMMT Feb 2025

    Mistral Medium 3—
    Qwen3.5 397B94.8%
    Source

    Not directly comparable

  • HMMT Nov 2025

    Mistral Medium 3—
    Qwen3.5 397B92.7%
    Source

    Not directly comparable

  • HMMT Feb 2026

    Mistral Medium 3—
    Qwen3.5 397B87.9%
    Source

    Not directly comparable

  • MMAnswerBench

    Mistral Medium 3—
    Qwen3.5 397B80.9%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    Mistral Medium 3—
    Qwen3.5 397B84.7%
    Source

    Not directly comparable

  • NOVA-63

    Mistral Medium 3—
    Qwen3.5 397B59.1%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Mistral Medium 3—
    Qwen3.5 397B79%
    Source

    Not directly comparable

  • MathVision

    Mistral Medium 3—
    Qwen3.5 397B88.6%
    Source

    Not directly comparable

  • CharXiv

    Mistral Medium 3—
    Qwen3.5 397B80.8%
    Source

    Not directly comparable

  • VideoMMMU

    Mistral Medium 3—
    Qwen3.5 397B84.7%
    Source

    Not directly comparable

  • ScreenSpot Pro

    Mistral Medium 3—
    Qwen3.5 397B65.6%
    Source

    Not directly comparable

  • V*

    Mistral Medium 3—
    Qwen3.5 397B95.8%
    Source

    Not directly comparable

Instruction following

  • IFEval

    Mistral Medium 3—
    Qwen3.5 397B92.6%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Mistral Medium 3 or Qwen3.5 397B?

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, Mistral Medium 3 or Qwen3.5 397B?

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, Mistral Medium 3 or Qwen3.5 397B?

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, Mistral Medium 3 or Qwen3.5 397B?

For the stated presets, chat costs $0.0014 on Mistral Medium 3 and $0.0024 on Qwen3.5 397B; repository review costs $0.026 and $0.0408; the cache-heavy agent loop costs $0.108 and $0.168. Mistral Medium 3 does not fit this workload in one request. Qwen3.5 397B does not fit this workload in one request. Mistral Medium 3 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Mistral Medium 3 or Qwen3.5 397B?

Both models list the same context window, 128K.

Related comparisons

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Last updated July 31, 2026

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