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Model comparison

MiMo-V2.5 vs Qwen3.8 Max

Updated August 3, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

MiMo-V2.5

Xiaomi

58.0/100

Estimated · Public rank #71

90% interval 46.4–69.5

Qwen3.8 Max

Alibaba

65.4/100

Estimated · Public rank #31

90% interval 55.5–75.3

Qwen3.8 Max has the higher public score estimate, 65.4 versus 57.95, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

4 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.

  • Coding work

    Code generation, repair, and software-engineering tasks

    Qwen3.8 Max

    Qwen3.8 Max leads on the same 1 weighted benchmark row.

    Confidence: limited

Show secondary and unsupported calls
  • 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

  • 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: listed-rates

  • 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
4
MiMo-V2.5 only
6
Qwen3.8 Max only
48
Like-for-like categories
2 / 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.

Coding

Like-for-like
MiMo-V2.5
56.1
Qwen3.8 Max
67.7
Weighted basis
1 vs 1 rows
Reading
Qwen3.8 Max leads

Multimodal

Like-for-like
MiMo-V2.5
79.0
Qwen3.8 Max
86.3
Weighted basis
2 vs 2 rows
Reading
Qwen3.8 Max leads

Agentic

Not comparable
MiMo-V2.5
65.8
Qwen3.8 Max
86.1
Weighted basis
1 vs 1 rows
Reading
Not comparable

Reasoning

Not comparable
MiMo-V2.5
Not measured
Qwen3.8 Max
78.3
Weighted basis
0 vs 2 rows
Reading
Not comparable

Knowledge

Not comparable
MiMo-V2.5
Not measured
Qwen3.8 Max
50.2
Weighted basis
0 vs 2 rows
Reading
Not comparable

Math

Not comparable
MiMo-V2.5
Not measured
Qwen3.8 Max
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
MiMo-V2.5
Not measured
Qwen3.8 Max
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
MiMo-V2.5
Not measured
Qwen3.8 Max
82.8
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.

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.

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

MiMo-V2.5
API rate not published
Fits in one request
Qwen3.8 Max
API rate not published
Fits in one request

MiMo-V2.5 has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

MiMo-V2.5
API rate not published
Fits in one request
Qwen3.8 Max
API rate not published
Fits in one request

MiMo-V2.5 has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

Cache-heavy agent loop

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

MiMo-V2.5
API rate not published
Fits in one request
Cached-input rate unavailable
Qwen3.8 Max
API rate not published
Fits in one request
Cached-input rate unavailable

MiMo-V2.5 has no comparable published API token rate. Qwen3.8 Max 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.

MiMo-V2.5

No comparable hosted API rate

Qwen3.8 Max

No comparable hosted API rate

Alibaba Cloud Model Studio pricing

Documented inputs

MiMo-V2.5

Not sourced

Qwen3.8 Max

Not sourced

Documented outputs

MiMo-V2.5

Not sourced

Qwen3.8 Max

Not sourced

Provider availability

MiMo-V2.5

Not sourced

Qwen3.8 Max

Not sourced

Reasoning profile

MiMo-V2.5

Reasoning

Qwen3.8 Max

Reasoning

Weight access

MiMo-V2.5

Proprietary

Qwen3.8 Max

Proprietary

License

MiMo-V2.5

Proprietary

Qwen3.8 Max

Proprietary

Release date

MiMo-V2.5

2026-04-22

Qwen3.8 Max

2026-08-03

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
Qwen3.8 Max has the higher public score estimate, 65.4 versus 57.95, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Both models list 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 evidence58 rows

Agentic

  • Claw-Eval

    MiMo-V2.562.3%
    Source
    Qwen3.8 Max

    Not directly comparable

  • MM-ClawBench

    MiMo-V2.523.8%
    Source
    Qwen3.8 Max

    Not directly comparable

  • Terminal-Bench 2.0

    MiMo-V2.565.8%
    Source
    Qwen3.8 Max

    Not directly comparable

  • Gert Labs

    MiMo-V2.546.89%
    Source
    Qwen3.8 Max

    Not directly comparable

  • ResearchClawBench

    MiMo-V2.516.9%
    Source
    Qwen3.8 Max

    Not directly comparable

  • Terminal-Bench 2.1

    MiMo-V2.5
    Qwen3.8 Max86.6%
    Source

    Not directly comparable

  • CoWorkBench

    MiMo-V2.5
    Qwen3.8 Max74.8%
    Source

    Not directly comparable

  • JobBench

    MiMo-V2.5
    Qwen3.8 Max53.4%
    Source

    Not directly comparable

  • skillsBench

    MiMo-V2.5
    Qwen3.8 Max70.2%
    Source

    Not directly comparable

  • Agents' Last Exam

    MiMo-V2.5
    Qwen3.8 Max52.4%
    Source

    Not directly comparable

  • AutomationBench

    MiMo-V2.5
    Qwen3.8 Max27.3%
    Source

    Not directly comparable

  • Toolathlon-Verified

    MiMo-V2.5
    Qwen3.8 Max72.5%
    Source

    Not directly comparable

  • WideResearch

    MiMo-V2.5
    Qwen3.8 Max81.9%
    Source

    Not directly comparable

  • HLE w/ tools

    MiMo-V2.5
    Qwen3.8 Max56.2%
    Source

    Not directly comparable

  • OSWorld-Verified

    MiMo-V2.5
    Qwen3.8 Max86.1%
    Source

    Not directly comparable

  • OSWorld 2.0

    MiMo-V2.5
    Qwen3.8 Max19.4%
    Source

    Not directly comparable

  • WebArena-Verified

    MiMo-V2.5
    Qwen3.8 Max66.8%
    Source

    Not directly comparable

  • AndroidWorld

    MiMo-V2.5
    Qwen3.8 Max85.3%
    Source

    Not directly comparable

  • MobileWorld

    MiMo-V2.5
    Qwen3.8 Max77.8%
    Source

    Not directly comparable

Coding

  • SWE-bench Pro

    MiMo-V2.556.1%
    Source
    Qwen3.8 Max67.7%
    Source

    Qwen3.8 Max leads this result

  • Terminal-Bench 2.0

    MiMo-V2.565.8%
    Source
    Qwen3.8 Max

    Not directly comparable

  • Terminal-Bench 2.1

    MiMo-V2.5
    Qwen3.8 Max86.6%
    Source

    Not directly comparable

  • deepSwe

    MiMo-V2.5
    Qwen3.8 Max56.6%
    Source

    Not directly comparable

  • NL2Repo

    MiMo-V2.5
    Qwen3.8 Max55.9%
    Source

    Not directly comparable

  • FrontierSWE

    MiMo-V2.5
    Qwen3.8 Max73.5%
    Source

    Not directly comparable

  • MLS-Bench Lite

    MiMo-V2.5
    Qwen3.8 Max41.0%
    Source

    Not directly comparable

  • PaperBench

    MiMo-V2.5
    Qwen3.8 Max93.0%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    MiMo-V2.5
    Qwen3.8 Max92.9%
    Source

    Not directly comparable

  • LongBench v2

    MiMo-V2.5
    Qwen3.8 Max66.3%
    Source

    Not directly comparable

Knowledge

  • GPQA

    MiMo-V2.5
    Qwen3.8 Max92.6%
    Source

    Not directly comparable

  • GPQA-D

    MiMo-V2.5
    Qwen3.8 Max92.6%
    Source

    Not directly comparable

  • HLE

    MiMo-V2.5
    Qwen3.8 Max43.6%
    Source

    Not directly comparable

  • HLE w/o tools

    MiMo-V2.5
    Qwen3.8 Max43.6%
    Source

    Not directly comparable

Multimodal

  • Video-MME (with subtitle)

    MiMo-V2.587.7%
    Source
    Qwen3.8 Max90.4%
    Source

    Qwen3.8 Max leads this result

  • CharXiv

    MiMo-V2.581%
    Source
    Qwen3.8 Max93.5%
    Source

    Qwen3.8 Max leads this result

  • MMMU-Pro

    MiMo-V2.577.9%
    Source
    Qwen3.8 Max82.3%
    Source

    Qwen3.8 Max leads this result

  • MathVision

    MiMo-V2.5
    Qwen3.8 Max95.2%
    Source

    Not directly comparable

  • MathVision w/ Python

    MiMo-V2.5
    Qwen3.8 Max97.7%
    Source

    Not directly comparable

  • BabyVision

    MiMo-V2.5
    Qwen3.8 Max82.0%
    Source

    Not directly comparable

  • BabyVision w/ Python

    MiMo-V2.5
    Qwen3.8 Max91.3%
    Source

    Not directly comparable

  • ZeroBench

    MiMo-V2.5
    Qwen3.8 Max24.0%
    Source

    Not directly comparable

  • ZeroBench w/ Python

    MiMo-V2.5
    Qwen3.8 Max49.0%
    Source

    Not directly comparable

  • MedXpertQA (MM)

    MiMo-V2.5
    Qwen3.8 Max80.4%
    Source

    Not directly comparable

  • ScreenSpot Pro

    MiMo-V2.5
    Qwen3.8 Max84.5%
    Source

    Not directly comparable

  • Vision2Web

    MiMo-V2.5
    Qwen3.8 Max69.0%
    Source

    Not directly comparable

  • CharXiv w/o tools

    MiMo-V2.5
    Qwen3.8 Max88.4%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    MiMo-V2.5
    Qwen3.8 Max92.1%
    Source

    Not directly comparable

  • OCRBench V2

    MiMo-V2.5
    Qwen3.8 Max74.2%
    Source

    Not directly comparable

  • CC-OCR

    MiMo-V2.5
    Qwen3.8 Max79.6%
    Source

    Not directly comparable

  • RealWorldQA

    MiMo-V2.5
    Qwen3.8 Max88.0%
    Source

    Not directly comparable

  • ERQA

    MiMo-V2.5
    Qwen3.8 Max77.8%
    Source

    Not directly comparable

  • SimpleVQA

    MiMo-V2.5
    Qwen3.8 Max75.0%
    Source

    Not directly comparable

  • PerceptionBench

    MiMo-V2.5
    Qwen3.8 Max63.5%
    Source

    Not directly comparable

  • VideoMMMU

    MiMo-V2.5
    Qwen3.8 Max88.7%
    Source

    Not directly comparable

  • MMVU

    MiMo-V2.5
    Qwen3.8 Max82.4%
    Source

    Not directly comparable

  • MLVU (M-Avg)

    MiMo-V2.5
    Qwen3.8 Max90.8%
    Source

    Not directly comparable

  • LVBench

    MiMo-V2.5
    Qwen3.8 Max81.8%
    Source

    Not directly comparable

Instruction following

  • IFBench

    MiMo-V2.5
    Qwen3.8 Max82.8%
    Source

    Not directly comparable

Frequently asked questions

Which is better, MiMo-V2.5 or Qwen3.8 Max?

Qwen3.8 Max has the higher public score estimate, 65.4 versus 57.95, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, MiMo-V2.5 or Qwen3.8 Max?

Qwen3.8 Max leads the like-for-like coding comparison across 1 shared weighted benchmark row.

Which is better for agentic tasks, MiMo-V2.5 or Qwen3.8 Max?

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, MiMo-V2.5 or Qwen3.8 Max?

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, MiMo-V2.5 or Qwen3.8 Max?

Both models list the same context window, 1M.

Related comparisons

Last updated August 3, 2026

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