Skip to main content
BenchLM
Data

Gemini 3.5 Flash vs MiMo-V2-Pro

Updated October 2, 2026. Rank says Gemini 3.5 Flash is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Share or export
Share on XLinkedInSocial cardCSVAPI/MCP

Decision reading

Gemini 3.5 Flash has the higher public point estimate, 63.95 versus 54.22. Their conditional score ranges overlap. These ranges do not establish rank confidence. 2 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

63.95/100

Supported · Public rank #41

90% interval 55.9–72.0

Model B
Xiaomi logo

Xiaomi

54.22/100

Estimated · Public rank #72

Conditional range 44.5–63.9

Shared results
2
Gemini 3.5 Flash only
25
MiMo-V2-Pro only
2
Like-for-like categories
0 / 8
Supported: Gemini 3.5 Flash · Estimated: MiMo-V2-Pro. 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.

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

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.

52.3Gemini 3.5 Flash41.5MiMo-V2-Pro

Directional only · BenchAlign v5.8

Gemini 3.5 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.

3 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 3.5 Flash
52.3
Supported · #39/144
MiMo-V2-Pro
41.5
Estimated · #62/144
Basis
BenchAlign v5.8 lane · 7 vs 1 public rows
Reading
Directional only

Knowledge

Directional only
Gemini 3.5 Flash
64.0
Supported · #30/171
MiMo-V2-Pro
48.5
Estimated · #71/171
Basis
BenchAlign v5.8 lane · 4 vs 0 public rows
Reading
Directional only

Instruction following

Directional only
Gemini 3.5 Flash
84.1
#43/125
MiMo-V2-Pro
82.6
#47/125
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Directional only

Agentic

Not comparable
Gemini 3.5 Flash
50.7
Supported · #42/119
MiMo-V2-Pro
Not ranked
Basis
BenchAlign v5.8 lane · 8 vs 3 public rows
Reading
Not comparable

Reasoning

Not comparable
Gemini 3.5 Flash
62.8
#20/27
MiMo-V2-Pro
69.2
Unranked · 2 rankable rows
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3.5 Flash
87.8
#6/49
MiMo-V2-Pro
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Multilingual

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

Math

Not comparable
Gemini 3.5 Flash
55.1
Unranked · 2 rankable rows
MiMo-V2-Pro
Not ranked
Basis
Provisional lane · 2 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 3.5 Flash
$0.006
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 3.5 Flash
$0.102
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 3.5 Flash
$0.15
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.

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 3.5 Flash

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 3.5 Flash

$0.15 per 1M cached input tokens

Google Gemini API pricing

MiMo-V2-Pro

No comparable hosted API rate

Documented inputs

Gemini 3.5 Flash

Not sourced

MiMo-V2-Pro

Not sourced

Documented outputs

Gemini 3.5 Flash

Not sourced

MiMo-V2-Pro

Not sourced

Provider availability

Gemini 3.5 Flash

Not sourced

MiMo-V2-Pro

Not sourced

Reasoning profile

Gemini 3.5 Flash

Reasoning

MiMo-V2-Pro

Reasoning

Weight access

Gemini 3.5 Flash

Proprietary

MiMo-V2-Pro

Proprietary

License

Gemini 3.5 Flash

Proprietary

MiMo-V2-Pro

Proprietary

Release date

Gemini 3.5 Flash

2026-05-19

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
Gemini 3.5 Flash has the higher public point estimate, 63.95 versus 54.22. 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
Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Gemini 3.5 Flash or MiMo-V2-Pro?

Gemini 3.5 Flash has the higher public point estimate, 63.95 versus 54.22. 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 3.5 Flash or MiMo-V2-Pro?

Gemini 3.5 Flash scores higher for coding on the public lane, 52.3 to 41.5. 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 3.5 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 3.5 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 3.5 Flash or MiMo-V2-Pro?

Both models list the same context window, 1M.

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

  • Terminal-Bench 2.1

    Gemini 3.5 Flash76.2%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • MCP Atlas

    Gemini 3.5 Flash83.6%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • Toolathlon

    Gemini 3.5 Flash56.5%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • OSWorld-Verified

    Gemini 3.5 Flash78.4%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • Finance Agent v2

    Gemini 3.5 Flash57.9%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • Gemini 3.5 Flash61.85%
    MiMo-V2-Pro36.68%

    Gemini 3.5 Flash leads this result

  • ResearchClawBench

    Shared source
    Gemini 3.5 Flash18.0%
    MiMo-V2-Pro15.3%

    Gemini 3.5 Flash leads this result

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.5 Flash74.2%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • Claw-Eval

    Gemini 3.5 Flash—
    MiMo-V2-Pro57.8%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.1

    Gemini 3.5 Flash76.2%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • SWE-bench Pro

    Gemini 3.5 Flash55.1%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • Vibe Code Bench

    Gemini 3.5 Flash48.68%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • cursorBench31

    Gemini 3.5 Flash49.8%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • CursorBench 3.2

    Gemini 3.5 Flash48.8%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • LiveCodeBench (Vals)

    Gemini 3.5 Flash87.6%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • SWE-bench (Vals)

    Gemini 3.5 Flash78.8%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • SWE-bench Verified

    Gemini 3.5 Flash—
    MiMo-V2-Pro78%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    Gemini 3.5 Flash77.3%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • MRCR 1M

    Gemini 3.5 Flash26.6%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • ARC-AGI-2

    Gemini 3.5 Flash72.1%
    Source
    MiMo-V2-Pro—

    Not directly comparable

Multimodal

  • CharXiv

    Gemini 3.5 Flash84.2%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • MMMU-Pro

    Gemini 3.5 Flash83.6%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • Blueprint-Bench 2

    Gemini 3.5 Flash33.6%
    Source
    MiMo-V2-Pro—

    Not directly comparable

Knowledge

  • GPQA-D

    Gemini 3.5 Flash92.7%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • HLE

    Gemini 3.5 Flash40.2%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • GPQA Diamond (Vals)

    Gemini 3.5 Flash92.7%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • MMLU-Pro (Vals)

    Gemini 3.5 Flash89.5%
    Source
    MiMo-V2-Pro—

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Gemini 3.5 Flash38.966%
    Source
    MiMo-V2-Pro—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Gemini 3.5 Flash14.583%
    Source
    MiMo-V2-Pro—

    Not directly comparable

29 public results · 2 shared

Watch Gemini 3.5 Flash vs MiMo-V2-Pro

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 2,000+ readers.

Last updated October 2, 2026