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Model A
Gemini 3 Flash

Google

62/100

Supported · Public rank #52

90% interval 48.375.7

Gemini 3 Flash vs MiMo-V2-Pro

Updated September 15, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Xiaomi logo
Model B
MiMo-V2-Pro

Xiaomi

62.79/100

Supported · Public rank #50

90% interval 51.973.7

Decision reading

MiMo-V2-Pro has the higher public score estimate, 62.79 versus 62, 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.

No workload recommendation clears the current evidence threshold.

Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.

Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    MiMo-V2-Pro 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-Pro is not ranked on the public lane for agentic, so no winner is named for agentic.

    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
2
Gemini 3 Flash only
9
MiMo-V2-Pro only
2
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.

Coding

Directional only
Gemini 3 Flash
41.4
Supported · #108/152
MiMo-V2-Pro
55.3
Estimated · #41/152
Basis
BenchAlign lane · 3 vs 1 public rows
Reading
Directional only

Knowledge

Directional only
Gemini 3 Flash
56.9
Supported · #45/183
MiMo-V2-Pro
53.5
Estimated · #63/183
Basis
BenchAlign lane · 2 vs 0 public rows
Reading
Directional only

Instruction following

Directional only
Gemini 3 Flash
66.2
#68/123
MiMo-V2-Pro
84.0
#49/123
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Directional only

Agentic

Not comparable
Gemini 3 Flash
33.9
Supported · #135/153
MiMo-V2-Pro
Not ranked
Basis
BenchAlign lane · 4 vs 3 public rows
Reading
Not comparable

Reasoning

Not comparable
Gemini 3 Flash
59.0
Unranked · 2 rankable rows
MiMo-V2-Pro
67.9
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3 Flash
50.2
Unranked · 2 rankable rows
MiMo-V2-Pro
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3 Flash
Not ranked
MiMo-V2-Pro
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3 Flash
75.8
Unranked · 1 rankable row
MiMo-V2-Pro
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.

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

Gemini 3 Flash
$0.002
Fits in one request
MiMo-V2-Pro
API rate not published
Fits in one request

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

Repository review

50K fresh input + 3K output tokens

Gemini 3 Flash
$0.034
Fits in one request
MiMo-V2-Pro
API rate not published
Fits in one request

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

Cache-heavy agent loop

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

Gemini 3 Flash
$0.05
Fits in one request
MiMo-V2-Pro
API rate not published
Fits in one request
Cached-input rate unavailable

MiMo-V2-Pro 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-Pro

1M

Cached-input rate

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

Gemini 3 Flash

$0.05 per 1M cached input tokens

Google Gemini API pricing

MiMo-V2-Pro

No comparable hosted API rate

Documented inputs

Gemini 3 Flash

Not sourced

MiMo-V2-Pro

Not sourced

Documented outputs

Gemini 3 Flash

Not sourced

MiMo-V2-Pro

Not sourced

Provider availability

Gemini 3 Flash

Not sourced

MiMo-V2-Pro

Not sourced

Reasoning profile

Gemini 3 Flash

Non-Reasoning

MiMo-V2-Pro

Reasoning

Weight access

Gemini 3 Flash

Proprietary

MiMo-V2-Pro

Proprietary

License

Gemini 3 Flash

Proprietary

MiMo-V2-Pro

Proprietary

Release date

Gemini 3 Flash

2025-12-01

MiMo-V2-Pro

2026-03-18

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-Pro has the higher public score estimate, 62.79 versus 62, 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 evidence13 rows

Agentic

  • Gemini 3 Flash49.2%
    MiMo-V2-Pro57.8%

    MiMo-V2-Pro leads this result

  • Gemini 3 Flash56.63%
    MiMo-V2-Pro36.68%

    Gemini 3 Flash leads this result

  • JobBench

    Gemini 3 Flash11.4%
    Source
    MiMo-V2-Pro

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Gemini 3 Flash53.9%
    Source
    MiMo-V2-Pro

    Not directly comparable

  • ResearchClawBench

    Gemini 3 Flash
    MiMo-V2-Pro15.3%
    Source

    Not directly comparable

Coding

  • Vibe Code Bench

    Gemini 3 Flash20.20%
    Source
    MiMo-V2-Pro

    Not directly comparable

  • LiveCodeBench (Vals)

    Gemini 3 Flash85.6%
    Source
    MiMo-V2-Pro

    Not directly comparable

  • SWE-bench (Vals)

    Gemini 3 Flash75.0%
    Source
    MiMo-V2-Pro

    Not directly comparable

  • SWE-bench Verified

    Gemini 3 Flash
    MiMo-V2-Pro78%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Gemini 3 Flash87.9%
    Source
    MiMo-V2-Pro

    Not directly comparable

  • MMLU-Pro (Vals)

    Gemini 3 Flash88.6%
    Source
    MiMo-V2-Pro

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Gemini 3 Flash35.640%
    Source
    MiMo-V2-Pro

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Gemini 3 Flash4.167%
    Source
    MiMo-V2-Pro

    Not directly comparable

Frequently asked questions

Which is better, Gemini 3 Flash or MiMo-V2-Pro?

MiMo-V2-Pro has the higher public score estimate, 62.79 versus 62, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Gemini 3 Flash or MiMo-V2-Pro?

MiMo-V2-Pro scores higher for coding on the public lane, 55.3 to 41.4. MiMo-V2-Pro 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, Gemini 3 Flash or MiMo-V2-Pro?

MiMo-V2-Pro is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Gemini 3 Flash or MiMo-V2-Pro?

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, Gemini 3 Flash or MiMo-V2-Pro?

Both models list the same context window, 1M.

Related comparisons

Last updated September 15, 2026

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