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Moonshot AI logo
Model A
Kimi K2.5

Moonshot AI

55.63/100

Supported · Public rank #103

90% interval 50.261.0

Kimi K2.5 vs MiMo-V2.5

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

Xiaomi logo
Model B
MiMo-V2.5

Xiaomi

60.72/100

Estimated · Public rank #68

90% interval 47.872.2

Decision reading

MiMo-V2.5 has the higher public score estimate, 60.72 versus 55.63, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

6 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

    Kimi K2.5 and MiMo-V2.5 are 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

    Kimi K2.5 and MiMo-V2.5 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: 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
6
Kimi K2.5 only
39
MiMo-V2.5 only
9
Like-for-like categories
0 / 8

4 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
Kimi K2.5
46.0
Estimated · #90/151
MiMo-V2.5
51.1
Estimated · #58/151
Basis
BenchAlign lane · 14 vs 6 public rows
Reading
Directional only

Coding

Directional only
Kimi K2.5
51.5
Estimated · #64/183
MiMo-V2.5
54.8
Estimated · #45/183
Basis
BenchAlign lane · 8 vs 4 public rows
Reading
Directional only

Knowledge

Directional only
Kimi K2.5
53.1
Estimated · #70/181
MiMo-V2.5
53.8
Estimated · #65/181
Basis
BenchAlign lane · 6 vs 2 public rows
Reading
Directional only

Multimodal

Directional only
Kimi K2.5
65.0
#24/48
MiMo-V2.5
58.5
#29/48
Basis
Provisional lane · 1 vs 2 weighted rows
Reading
Directional only

Reasoning

Not comparable
Kimi K2.5
53.5
Unranked · 3 rankable rows
MiMo-V2.5
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Kimi K2.5
62.4
#5/7
MiMo-V2.5
Not ranked
Basis
Provisional lane · 4 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Kimi K2.5
38.2
#8/12
MiMo-V2.5
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Kimi K2.5
85.6
#40/120
MiMo-V2.5
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.

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

Kimi K2.5
$0.0021
Fits in one request
MiMo-V2.5
API rate not published
Fits in one request

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

Repository review

50K fresh input + 3K output tokens

Kimi K2.5
$0.039
Fits in one request
MiMo-V2.5
API rate not published
Fits in one request

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

Cache-heavy agent loop

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

Kimi K2.5
$0.162
Fits in one request
Cached input priced at the published list-input rate
MiMo-V2.5
API rate not published
Fits in one request
Cached-input rate unavailable

Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate. MiMo-V2.5 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.

Kimi K2.5

256K

MiMo-V2.5

1M

API model ID

Kimi K2.5

Not sourced

MiMo-V2.5

Not sourced

Cached-input rate

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

Kimi K2.5

Not published

MiMo-V2.5

No comparable hosted API rate

Documented inputs

Kimi K2.5

Not sourced

MiMo-V2.5

Not sourced

Documented outputs

Kimi K2.5

Not sourced

MiMo-V2.5

Not sourced

Provider availability

Kimi K2.5

Not sourced

MiMo-V2.5

Not sourced

Reasoning profile

Kimi K2.5

Non-Reasoning

MiMo-V2.5

Reasoning

Weight access

Kimi K2.5

Open Weight

MiMo-V2.5

Proprietary

License

Kimi K2.5

Open Weight

MiMo-V2.5

Proprietary

Release date

Kimi K2.5

2026-02-01

MiMo-V2.5

2026-04-22

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 55.63, 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.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Kimi K2.5
API / mo$2,700
Self-host / mo$5,221
Break-even132M/day
MiMo-V2.5
API / mo$0
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Model the full break-even

Benchmark evidence

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

Browse raw public benchmark evidence54 rows

Agentic

  • Terminal-Bench 2.0

    Kimi K2.550.8%
    Source
    MiMo-V2.565.8%
    Source

    MiMo-V2.5 leads this result

  • BrowseComp

    Kimi K2.560.6%
    Source
    MiMo-V2.5

    Not directly comparable

  • Kimi K2.552.3%
    MiMo-V2.562.3%

    MiMo-V2.5 leads this result

  • QwenClawBench

    Kimi K2.554.3%
    Source
    MiMo-V2.5

    Not directly comparable

  • τ³-bench results

    Kimi K2.565.7%
    Source
    MiMo-V2.5

    Not directly comparable

  • DeepSearchQA

    Kimi K2.577.1%
    Source
    MiMo-V2.5

    Not directly comparable

  • DeepPlanning

    Kimi K2.514.4%
    Source
    MiMo-V2.5

    Not directly comparable

  • Toolathlon

    Kimi K2.527.8%
    Source
    MiMo-V2.5

    Not directly comparable

  • MCP Atlas

    Kimi K2.529.5%
    Source
    MiMo-V2.5

    Not directly comparable

  • MCP-Tasks

    Kimi K2.559.1%
    Source
    MiMo-V2.5

    Not directly comparable

  • WideResearch

    Kimi K2.572.7%
    Source
    MiMo-V2.5

    Not directly comparable

  • Kimi K2.545.88%
    MiMo-V2.546.89%

    MiMo-V2.5 leads this result

  • ResearchClawBench

    Shared source
    Kimi K2.514.0%
    MiMo-V2.516.9%

    MiMo-V2.5 leads this result

  • JobBench

    Kimi K2.58.7%
    Source
    MiMo-V2.5

    Not directly comparable

  • MM-ClawBench

    Kimi K2.5
    MiMo-V2.523.8%
    Source

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Kimi K2.5
    MiMo-V2.560.7%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Kimi K2.576.8%
    Source
    MiMo-V2.5

    Not directly comparable

  • SWE-bench Verified*

    Kimi K2.570.8%
    Source
    MiMo-V2.5

    Not directly comparable

  • LiveCodeBench v6

    Kimi K2.585.0%
    Source
    MiMo-V2.5

    Not directly comparable

  • SWE-bench Pro

    Kimi K2.550.7%
    Source
    MiMo-V2.556.1%
    Source

    MiMo-V2.5 leads this result

  • SWE Multilingual

    Kimi K2.573%
    Source
    MiMo-V2.5

    Not directly comparable

  • SWE-Rebench

    Kimi K2.558.5%
    Source
    MiMo-V2.5

    Not directly comparable

  • React Native Evals

    Kimi K2.577.2%
    Source
    MiMo-V2.5

    Not directly comparable

  • SciCode

    Kimi K2.548.7%
    Source
    MiMo-V2.5

    Not directly comparable

  • Terminal-Bench 2.0

    Kimi K2.5
    MiMo-V2.565.8%
    Source

    Not directly comparable

  • LiveCodeBench (Vals)

    Kimi K2.5
    MiMo-V2.581.5%
    Source

    Not directly comparable

  • SWE-bench (Vals)

    Kimi K2.5
    MiMo-V2.571.0%
    Source

    Not directly comparable

Reasoning

  • LongBench v2

    Kimi K2.561%
    Source
    MiMo-V2.5

    Not directly comparable

Knowledge

  • GPQA

    Kimi K2.587.6%
    Source
    MiMo-V2.5

    Not directly comparable

  • GPQA-D

    Kimi K2.587.6%
    Source
    MiMo-V2.5

    Not directly comparable

  • SuperGPQA

    Kimi K2.569.2%
    Source
    MiMo-V2.5

    Not directly comparable

  • MMLU-Pro

    Kimi K2.587.1%
    Source
    MiMo-V2.5

    Not directly comparable

  • MMLU-Pro (Arcee)

    Kimi K2.587.1%
    Source
    MiMo-V2.5

    Not directly comparable

  • HLE

    Kimi K2.530.1%
    Source
    MiMo-V2.5

    Not directly comparable

  • GPQA Diamond (Vals)

    Kimi K2.5
    MiMo-V2.581.6%
    Source

    Not directly comparable

  • MMLU-Pro (Vals)

    Kimi K2.5
    MiMo-V2.582.9%
    Source

    Not directly comparable

Math

  • AIME 2025

    Kimi K2.596.1%
    Source
    MiMo-V2.5

    Not directly comparable

  • AIME26

    Kimi K2.595.8%
    Source
    MiMo-V2.5

    Not directly comparable

  • AIME25 (Arcee)

    Kimi K2.596.3%
    Source
    MiMo-V2.5

    Not directly comparable

  • HMMT Feb 2025

    Kimi K2.595.4%
    Source
    MiMo-V2.5

    Not directly comparable

  • HMMT Nov 2025

    Kimi K2.591.1%
    Source
    MiMo-V2.5

    Not directly comparable

  • HMMT Feb 2026

    Kimi K2.587.1%
    Source
    MiMo-V2.5

    Not directly comparable

  • MMAnswerBench

    Kimi K2.581.8%
    Source
    MiMo-V2.5

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Kimi K2.527.900%
    Source
    MiMo-V2.5

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Kimi K2.54.200%
    Source
    MiMo-V2.5

    Not directly comparable

Multilingual

  • MMLU-ProX

    Kimi K2.582.3%
    Source
    MiMo-V2.5

    Not directly comparable

  • NOVA-63

    Kimi K2.556.0%
    Source
    MiMo-V2.5

    Not directly comparable

Multimodal

  • MMMU-Pro

    Kimi K2.578.5%
    Source
    MiMo-V2.577.9%
    Source

    Kimi K2.5 leads this result

  • Video-MME

    Kimi K2.587.4%
    Source
    MiMo-V2.5

    Not directly comparable

  • MMVU

    Kimi K2.580.4%
    Source
    MiMo-V2.5

    Not directly comparable

  • VideoMMMU

    Kimi K2.586.6%
    Source
    MiMo-V2.5

    Not directly comparable

  • Video-MME (with subtitle)

    Kimi K2.5
    MiMo-V2.587.7%
    Source

    Not directly comparable

  • CharXiv

    Kimi K2.5
    MiMo-V2.581%
    Source

    Not directly comparable

Instruction following

  • IFEval

    Kimi K2.593.9%
    Source
    MiMo-V2.5

    Not directly comparable

Frequently asked questions

Which is better, Kimi K2.5 or MiMo-V2.5?

MiMo-V2.5 has the higher public score estimate, 60.72 versus 55.63, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Kimi K2.5 or MiMo-V2.5?

MiMo-V2.5 scores higher for coding on the public lane, 54.8 to 51.5. Kimi K2.5 and MiMo-V2.5 are 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, Kimi K2.5 or MiMo-V2.5?

MiMo-V2.5 scores higher for agentic tasks on the public lane, 51.1 to 46. Kimi K2.5 and MiMo-V2.5 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, Kimi K2.5 or MiMo-V2.5?

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, Kimi K2.5 or MiMo-V2.5?

MiMo-V2.5 has the larger documented context window: 1M, compared with 256K.

Related comparisons

Last updated September 4, 2026

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