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Radar

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BenchLM
Xiaomi logo
Model A
MiMo-V2.5

Xiaomi

60.72/100

Estimated · Public rank #68

90% interval 47.8–72.2

MiMo-V2.5 vs Qwen3.5-35B-A3B

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

Alibaba logo
Model B
Qwen3.5-35B-A3B

Alibaba

54.86/100

Supported · Public rank #108

90% interval 45.1–64.6

Decision reading

MiMo-V2.5 has the higher public score estimate, 60.72 versus 54.86, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

2 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

    MiMo-V2.5

    MiMo-V2.5 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

    MiMo-V2.5 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    MiMo-V2.5 and Qwen3.5-35B-A3B are scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    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: 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
2
MiMo-V2.5 only
13
Qwen3.5-35B-A3B only
14
Like-for-like categories
0 / 8

3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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

Directional only
MiMo-V2.5
51.1
Estimated · #58/151
Qwen3.5-35B-A3B
46.0
Estimated · #89/151
Basis
BenchAlign lane · 6 vs 4 public rows
Reading
Directional only

Coding

Directional only
MiMo-V2.5
54.8
Estimated · #45/183
Qwen3.5-35B-A3B
30.2
Supported · #168/183
Basis
BenchAlign lane · 4 vs 2 public rows
Reading
Directional only

Knowledge

Directional only
MiMo-V2.5
53.8
Estimated · #65/181
Qwen3.5-35B-A3B
46.1
Supported · #110/181
Basis
BenchAlign lane · 2 vs 3 public rows
Reading
Directional only

Reasoning

Not comparable
MiMo-V2.5
Not ranked
Qwen3.5-35B-A3B
40.0
Unranked · 3 rankable rows
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Math

Not comparable
MiMo-V2.5
Not ranked
Qwen3.5-35B-A3B
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
MiMo-V2.5
Not ranked
Qwen3.5-35B-A3B
21.1
#11/12
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multimodal

Not comparable
MiMo-V2.5
58.5
#29/48
Qwen3.5-35B-A3B
66.8
Unranked · 3 rankable rows
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
MiMo-V2.5
Not ranked
Qwen3.5-35B-A3B
88.5
#29/120
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.

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
Qwen3.5-35B-A3B
Self-hosted; infrastructure cost varies
Fits in one request

MiMo-V2.5 has no comparable published API token rate. Qwen3.5-35B-A3B 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
Qwen3.5-35B-A3B
Self-hosted; infrastructure cost varies
Fits in one request

MiMo-V2.5 has no comparable published API token rate. Qwen3.5-35B-A3B 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
Qwen3.5-35B-A3B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

MiMo-V2.5 has no comparable published API token rate. Qwen3.5-35B-A3B 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.

Context window

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

MiMo-V2.5

1M

Qwen3.5-35B-A3B

262K

API model ID

MiMo-V2.5

Not sourced

Qwen3.5-35B-A3B

Not sourced

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

Qwen3.5-35B-A3B

No comparable hosted API rate

Documented inputs

MiMo-V2.5

Not sourced

Qwen3.5-35B-A3B

Not sourced

Documented outputs

MiMo-V2.5

Not sourced

Qwen3.5-35B-A3B

Not sourced

Provider availability

MiMo-V2.5

Not sourced

Qwen3.5-35B-A3B

Not sourced

Reasoning profile

MiMo-V2.5

Reasoning

Qwen3.5-35B-A3B

Reasoning

Weight access

MiMo-V2.5

Proprietary

Qwen3.5-35B-A3B

Open Weight

License

MiMo-V2.5

Proprietary

Qwen3.5-35B-A3B

Open Weight

Release date

MiMo-V2.5

2026-04-22

Qwen3.5-35B-A3B

2026-03-04

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
MiMo-V2.5 has the higher public score estimate, 60.72 versus 54.86, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
MiMo-V2.5 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 evidence29 rows

Agentic

  • Claw-Eval

    MiMo-V2.562.3%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • MM-ClawBench

    MiMo-V2.523.8%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • Terminal-Bench 2.0

    MiMo-V2.565.8%
    Source
    Qwen3.5-35B-A3B40.5%
    Source

    MiMo-V2.5 leads this result

  • Gert Labs

    Shared source
    MiMo-V2.546.89%
    Qwen3.5-35B-A3B28.96%

    MiMo-V2.5 leads this result

  • ResearchClawBench

    MiMo-V2.516.9%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    MiMo-V2.560.7%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • BrowseComp

    MiMo-V2.5—
    Qwen3.5-35B-A3B61%
    Source

    Not directly comparable

  • OSWorld-Verified

    MiMo-V2.5—
    Qwen3.5-35B-A3B54.5%
    Source

    Not directly comparable

Coding

  • SWE-bench Pro

    MiMo-V2.556.1%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • Terminal-Bench 2.0

    MiMo-V2.565.8%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • LiveCodeBench (Vals)

    MiMo-V2.581.5%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • SWE-bench (Vals)

    MiMo-V2.571.0%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • SWE-bench Verified

    MiMo-V2.5—
    Qwen3.5-35B-A3B69.2%
    Source

    Not directly comparable

  • SWE-Rebench

    MiMo-V2.5—
    Qwen3.5-35B-A3B53.7%
    Source

    Not directly comparable

Reasoning

  • LongBench v2

    MiMo-V2.5—
    Qwen3.5-35B-A3B59%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    MiMo-V2.581.6%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • MMLU-Pro (Vals)

    MiMo-V2.582.9%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • MMLU-Pro

    MiMo-V2.5—
    Qwen3.5-35B-A3B85.3%
    Source

    Not directly comparable

  • SuperGPQA

    MiMo-V2.5—
    Qwen3.5-35B-A3B63.4%
    Source

    Not directly comparable

  • GPQA

    MiMo-V2.5—
    Qwen3.5-35B-A3B84.2%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    MiMo-V2.5—
    Qwen3.5-35B-A3B81%
    Source

    Not directly comparable

Multimodal

  • Video-MME (with subtitle)

    MiMo-V2.587.7%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • CharXiv

    MiMo-V2.581%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • MMMU-Pro

    MiMo-V2.577.9%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • MMMU

    MiMo-V2.5—
    Qwen3.5-35B-A3B81.4%
    Source

    Not directly comparable

  • MMVU

    MiMo-V2.5—
    Qwen3.5-35B-A3B72.3%
    Source

    Not directly comparable

  • MathVision

    MiMo-V2.5—
    Qwen3.5-35B-A3B83.9%
    Source

    Not directly comparable

  • V*

    MiMo-V2.5—
    Qwen3.5-35B-A3B92.7%
    Source

    Not directly comparable

Instruction following

  • IFEval

    MiMo-V2.5—
    Qwen3.5-35B-A3B91.9%
    Source

    Not directly comparable

Frequently asked questions

Which is better, MiMo-V2.5 or Qwen3.5-35B-A3B?

MiMo-V2.5 has the higher public score estimate, 60.72 versus 54.86, 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 Qwen3.5-35B-A3B?

MiMo-V2.5 scores higher for coding on the public lane, 54.8 to 30.2. MiMo-V2.5 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, MiMo-V2.5 or Qwen3.5-35B-A3B?

MiMo-V2.5 scores higher for agentic tasks on the public lane, 51.1 to 46. MiMo-V2.5 and Qwen3.5-35B-A3B are scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, MiMo-V2.5 or Qwen3.5-35B-A3B?

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 Qwen3.5-35B-A3B?

MiMo-V2.5 has the larger documented context window: 1M, compared with 262K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 4, 2026

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