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Gemini 3.1 Flash-Lite vs MiMo-V2-Flash

Updated October 17, 2026. Rank says Gemini 3.1 Flash-Lite is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

Gemini 3.1 Flash-Lite has the higher public point estimate, 46.96 versus 41. Their conditional score ranges overlap. These ranges do not establish rank confidence. 1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Google logo

Google

46.96/100

Estimated · Public rank #107

Conditional range 37.2–56.7

Model B
Xiaomi logo

Xiaomi

41/100

Estimated · Public rank #131

Conditional range 31.3–50.7

Shared results
1
Gemini 3.1 Flash-Lite only
10
MiMo-V2-Flash only
7
Like-for-like categories
0 / 8
Estimated: Gemini 3.1 Flash-Lite and MiMo-V2-Flash. Conditional ranges do not establish rank confidence.How the comparison works

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

    Gemini 3.1 Flash-Lite

    Gemini 3.1 Flash-Lite 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

    Gemini 3.1 Flash-Lite and MiMo-V2-Flash 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

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

    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

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

27.2Gemini 3.1 Flash-Lite28.5MiMo-V2-Flash

Directional only · BenchAlign v5.8

MiMo-V2-Flash has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

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

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.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 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 3.1 Flash-Lite
27.2
Estimated · #101/150
MiMo-V2-Flash
28.5
Estimated · #98/150
Basis
BenchAlign v5.8 lane · 3 vs 3 public rows
Reading
Directional only

Knowledge

Directional only
Gemini 3.1 Flash-Lite
46.9
Estimated · #89/184
MiMo-V2-Flash
34.9
Supported · #135/184
Basis
BenchAlign v5.8 lane · 2 vs 3 public rows
Reading
Directional only

Agentic

Not comparable
Gemini 3.1 Flash-Lite
27.4
Estimated · #100/128
MiMo-V2-Flash
Not ranked
Basis
BenchAlign v5.8 lane · 2 vs 0 public rows
Reading
Not comparable

Reasoning

Not comparable
Gemini 3.1 Flash-Lite
Not ranked
MiMo-V2-Flash
58.1
Unranked · 3 rankable rows
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3.1 Flash-Lite
42.0
Unranked · 1 rankable row
MiMo-V2-Flash
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.1 Flash-Lite
Not ranked
MiMo-V2-Flash
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.1 Flash-Lite
Not ranked
MiMo-V2-Flash
46.3
#102/148
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3.1 Flash-Lite
44.0
Unranked · 1 rankable row
MiMo-V2-Flash
Not ranked
Basis
Provisional lane · 1 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 v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

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 3.1 Flash-Lite
$0.001
Fits in one request
MiMo-V2-Flash
Self-hosted; infrastructure cost varies
Fits in one request

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

Repository review

50K fresh input + 3K output tokens

Gemini 3.1 Flash-Lite
$0.017
Fits in one request
MiMo-V2-Flash
Self-hosted; infrastructure cost varies
Fits in one request

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

Cache-heavy agent loop

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

Gemini 3.1 Flash-Lite
$0.025
Fits in one request
MiMo-V2-Flash
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

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

Cached input falls back to the list input rate only where a cached rate is unpublished

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.

Gemini 3.1 Flash-Lite

MiMo-V2-Flash

256K

Cached-input rate

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

Gemini 3.1 Flash-Lite

$0.025 per 1M cached input tokens

Google Gemini API pricing

MiMo-V2-Flash

No comparable hosted API rate

Documented inputs

Gemini 3.1 Flash-Lite

Not sourced

MiMo-V2-Flash

Not sourced

Documented outputs

Gemini 3.1 Flash-Lite

Not sourced

MiMo-V2-Flash

Not sourced

Provider availability

Gemini 3.1 Flash-Lite

Not sourced

MiMo-V2-Flash

Not sourced

Reasoning profile

Gemini 3.1 Flash-Lite

Non-Reasoning

MiMo-V2-Flash

Reasoning

Weight access

Gemini 3.1 Flash-Lite

Proprietary

MiMo-V2-Flash

Open Weight

License

Gemini 3.1 Flash-Lite

Proprietary

MiMo-V2-Flash

Open Weight

Release date

Gemini 3.1 Flash-Lite

2026-03-03

MiMo-V2-Flash

2026-03-15

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
Gemini 3.1 Flash-Lite has the higher public point estimate, 46.96 versus 41. Their conditional score ranges overlap. These ranges do not establish rank confidence.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Gemini 3.1 Flash-Lite has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Gemini 3.1 Flash-Lite or MiMo-V2-Flash?

Gemini 3.1 Flash-Lite has the higher public point estimate, 46.96 versus 41. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Gemini 3.1 Flash-Lite or MiMo-V2-Flash?

MiMo-V2-Flash scores higher for coding on the public lane, 28.5 to 27.2. Gemini 3.1 Flash-Lite and MiMo-V2-Flash 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, Gemini 3.1 Flash-Lite or MiMo-V2-Flash?

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

Which costs less, Gemini 3.1 Flash-Lite or MiMo-V2-Flash?

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 3.1 Flash-Lite or MiMo-V2-Flash?

Gemini 3.1 Flash-Lite has the larger documented context window: 1M, compared with 256K.

Benchmark evidence

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

Browse raw public benchmark evidence18 rows

Agentic

  • Gert Labs

    Gemini 3.1 Flash-Lite38.46%
    Source
    MiMo-V2-Flash—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.1 Flash-Lite34.1%
    Source
    MiMo-V2-Flash—

    Not directly comparable

Coding

  • Vibe Code Bench

    Gemini 3.1 Flash-Lite0.00%
    Source
    MiMo-V2-Flash—

    Not directly comparable

  • LiveCodeBench (Vals)

    Gemini 3.1 Flash-Lite80.1%
    Source
    MiMo-V2-Flash—

    Not directly comparable

  • SWE-bench (Vals)

    Gemini 3.1 Flash-Lite62.8%
    Source
    MiMo-V2-Flash—

    Not directly comparable

  • SWE-bench Verified

    Gemini 3.1 Flash-Lite—
    MiMo-V2-Flash73.4%
    Source

    Not directly comparable

  • LiveCodeBench v6

    Gemini 3.1 Flash-Lite—
    MiMo-V2-Flash80.6%
    Source

    Not directly comparable

  • SWE Multilingual

    Gemini 3.1 Flash-Lite—
    MiMo-V2-Flash71.7%
    Source

    Not directly comparable

Reasoning

  • JevBench 1.4

    Gemini 3.1 Flash-Lite14.26
    Source
    MiMo-V2-Flash—

    Not directly comparable

  • JevBench 1.5

    Gemini 3.1 Flash-Lite19.58
    Source
    MiMo-V2-Flash—

    Not directly comparable

  • LongBench v2

    Gemini 3.1 Flash-Lite—
    MiMo-V2-Flash60.6%
    Source

    Not directly comparable

Multimodal

  • CharXiv

    Gemini 3.1 Flash-Lite73.2%
    Source
    MiMo-V2-Flash—

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Gemini 3.1 Flash-Lite81.1%
    Source
    MiMo-V2-Flash59.3%
    Source

    Gemini 3.1 Flash-Lite leads this result

  • MMLU-Pro (Vals)

    Gemini 3.1 Flash-Lite86.2%
    Source
    MiMo-V2-Flash—

    Not directly comparable

  • GPQA

    Gemini 3.1 Flash-Lite—
    MiMo-V2-Flash83.7%
    Source

    Not directly comparable

  • MMLU-Pro

    Gemini 3.1 Flash-Lite—
    MiMo-V2-Flash84.9%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Gemini 3.1 Flash-Lite27.719%
    Source
    MiMo-V2-Flash—

    Not directly comparable

  • AIME 2025

    Gemini 3.1 Flash-Lite—
    MiMo-V2-Flash94.1%
    Source

    Not directly comparable

18 public results · 1 shared

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Last updated October 17, 2026