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Model A
Gemini 3.5 Flash-Lite

Google

60.5/100

Supported · Public rank #72

90% interval 49.072.0

Gemini 3.5 Flash-Lite 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 60.5, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

8 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-V2.5 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

    Gemini 3.5 Flash-Lite and MiMo-V2.5 are scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    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
8
Gemini 3.5 Flash-Lite only
2
MiMo-V2.5 only
7
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
Gemini 3.5 Flash-Lite
43.4
Estimated · #104/151
MiMo-V2.5
51.1
Estimated · #58/151
Basis
BenchAlign lane · 3 vs 6 public rows
Reading
Directional only

Coding

Directional only
Gemini 3.5 Flash-Lite
43.6
Supported · #121/183
MiMo-V2.5
54.8
Estimated · #45/183
Basis
BenchAlign lane · 4 vs 4 public rows
Reading
Directional only

Knowledge

Directional only
Gemini 3.5 Flash-Lite
53.0
Supported · #71/181
MiMo-V2.5
53.8
Estimated · #65/181
Basis
BenchAlign lane · 2 vs 2 public rows
Reading
Directional only

Multimodal

Directional only
Gemini 3.5 Flash-Lite
76.1
#16/48
MiMo-V2.5
58.5
#29/48
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Directional only

Reasoning

Not comparable
Gemini 3.5 Flash-Lite
60.8
Unranked · 3 rankable rows
MiMo-V2.5
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
MiMo-V2.5
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
MiMo-V2.5
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
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

Gemini 3.5 Flash-Lite
$0.00155
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

Gemini 3.5 Flash-Lite
$0.0225
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

Gemini 3.5 Flash-Lite
$0.037
Fits in one request
MiMo-V2.5
API rate not published
Fits in one request
Cached-input rate unavailable

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.

Cached-input rate

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

Gemini 3.5 Flash-Lite

$0.03 per 1M cached input tokens

Google Gemini API pricing

MiMo-V2.5

No comparable hosted API rate

Reasoning profile

Gemini 3.5 Flash-Lite

Reasoning

MiMo-V2.5

Reasoning

Weight access

Gemini 3.5 Flash-Lite

Proprietary

MiMo-V2.5

Proprietary

License

Gemini 3.5 Flash-Lite

Proprietary

MiMo-V2.5

Proprietary

Release date

Gemini 3.5 Flash-Lite

2026-07-21

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 60.5, 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 evidence17 rows

Agentic

  • Terminal-Bench 2.0

    Gemini 3.5 Flash-Lite54%
    Source
    MiMo-V2.565.8%
    Source

    MiMo-V2.5 leads this result

  • OSWorld-Verified

    Gemini 3.5 Flash-Lite74%
    Source
    MiMo-V2.5

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.5 Flash-Lite50.2%
    Source
    MiMo-V2.560.7%
    Source

    MiMo-V2.5 leads this result

  • Claw-Eval

    Gemini 3.5 Flash-Lite
    MiMo-V2.562.3%
    Source

    Not directly comparable

  • MM-ClawBench

    Gemini 3.5 Flash-Lite
    MiMo-V2.523.8%
    Source

    Not directly comparable

  • Gert Labs

    Gemini 3.5 Flash-Lite
    MiMo-V2.546.89%
    Source

    Not directly comparable

  • ResearchClawBench

    Gemini 3.5 Flash-Lite
    MiMo-V2.516.9%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.0

    Gemini 3.5 Flash-Lite54.0%
    Source
    MiMo-V2.565.8%
    Source

    MiMo-V2.5 leads this result

  • SWE-bench Pro

    Gemini 3.5 Flash-Lite54.2%
    Source
    MiMo-V2.556.1%
    Source

    MiMo-V2.5 leads this result

  • LiveCodeBench (Vals)

    Gemini 3.5 Flash-Lite79.0%
    Source
    MiMo-V2.581.5%
    Source

    MiMo-V2.5 leads this result

  • SWE-bench (Vals)

    Gemini 3.5 Flash-Lite75.0%
    Source
    MiMo-V2.571.0%
    Source

    Gemini 3.5 Flash-Lite leads this result

Reasoning

  • MRCRv2

    Gemini 3.5 Flash-Lite72.2%
    Source
    MiMo-V2.5

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Gemini 3.5 Flash-Lite83.8%
    Source
    MiMo-V2.581.6%
    Source

    Gemini 3.5 Flash-Lite leads this result

  • MMLU-Pro (Vals)

    Gemini 3.5 Flash-Lite85.8%
    Source
    MiMo-V2.582.9%
    Source

    Gemini 3.5 Flash-Lite leads this result

Multimodal

  • Video-MME (with subtitle)

    Gemini 3.5 Flash-Lite
    MiMo-V2.587.7%
    Source

    Not directly comparable

  • CharXiv

    Gemini 3.5 Flash-Lite
    MiMo-V2.581%
    Source

    Not directly comparable

  • MMMU-Pro

    Gemini 3.5 Flash-Lite
    MiMo-V2.577.9%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Gemini 3.5 Flash-Lite or MiMo-V2.5?

MiMo-V2.5 has the higher public score estimate, 60.72 versus 60.5, 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 3.5 Flash-Lite or MiMo-V2.5?

MiMo-V2.5 scores higher for coding on the public lane, 54.8 to 43.6. 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, Gemini 3.5 Flash-Lite or MiMo-V2.5?

MiMo-V2.5 scores higher for agentic tasks on the public lane, 51.1 to 43.4. Gemini 3.5 Flash-Lite 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, Gemini 3.5 Flash-Lite 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, Gemini 3.5 Flash-Lite or MiMo-V2.5?

Both models list the same context window, 1M.

Related comparisons

Last updated September 4, 2026

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