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Model comparison

Gemini 3.5 Flash vs Kimi-Audio 7B

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

Gemini 3.5 Flash

Google

64.0/100

Estimated · Public rank #38

90% interval 53.4–74.8

Kimi-Audio 7B

Moonshot AI

Evidence status unavailable

90% interval unavailable

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.

0 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

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

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    Not enough matched evidence

    A complete context comparison is not sourced.

    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

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
0
Gemini 3.5 Flash only
22
Kimi-Audio 7B only
0
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Agentic

Not comparable
Gemini 3.5 Flash
77.2
Kimi-Audio 7B
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Gemini 3.5 Flash
55.1
Kimi-Audio 7B
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Gemini 3.5 Flash
74.7
Kimi-Audio 7B
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Gemini 3.5 Flash
40.2
Kimi-Audio 7B
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Math

Not comparable
Gemini 3.5 Flash
32.9
Kimi-Audio 7B
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.5 Flash
Not measured
Kimi-Audio 7B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3.5 Flash
83.8
Kimi-Audio 7B
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.5 Flash
Not measured
Kimi-Audio 7B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

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 3.5 Flash
$0.006
Fits in one request
Kimi-Audio 7B
API rate not published
Fit state unavailable

Kimi-Audio 7B 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
Kimi-Audio 7B
API rate not published
Fit state unavailable

Kimi-Audio 7B 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
Kimi-Audio 7B
API rate not published
Fit state unavailable
Cached-input rate unavailable

Kimi-Audio 7B 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.

Gemini 3.5 Flash

Kimi-Audio 7B

N/A

Documented inputs

Gemini 3.5 Flash

Not sourced

Kimi-Audio 7B

Not sourced

Documented outputs

Gemini 3.5 Flash

Not sourced

Kimi-Audio 7B

Not sourced

Provider availability

Gemini 3.5 Flash

Not sourced

Kimi-Audio 7B

Not sourced

Reasoning profile

Gemini 3.5 Flash

Reasoning

Kimi-Audio 7B

Non-Reasoning

Weight access

Gemini 3.5 Flash

Proprietary

Kimi-Audio 7B

Open Weight

License

Gemini 3.5 Flash

Proprietary

Kimi-Audio 7B

Open Weight

Release date

Gemini 3.5 Flash

2026-05-19

Kimi-Audio 7B

2025-04-25

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
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
A complete documented context comparison is not available.

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 evidence22 rows

Agentic

  • Terminal-Bench 2.0

    Gemini 3.5 Flash76.2%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • MCP Atlas

    Gemini 3.5 Flash83.6%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • Toolathlon

    Gemini 3.5 Flash56.5%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • OSWorld-Verified

    Gemini 3.5 Flash78.4%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • Finance Agent v2

    Gemini 3.5 Flash57.9%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • Gert Labs

    Gemini 3.5 Flash61.85%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • ResearchClawBench

    Gemini 3.5 Flash18.0%
    Source
    Kimi-Audio 7B

    Not directly comparable

Coding

  • Terminal-Bench 2.0

    Gemini 3.5 Flash76.2%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • SWE-bench Pro

    Gemini 3.5 Flash55.1%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • Vibe Code Bench

    Gemini 3.5 Flash48.68%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • cursorBench31

    Gemini 3.5 Flash49.8%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • cursorBench32

    Gemini 3.5 Flash48.8%
    Source
    Kimi-Audio 7B

    Not directly comparable

Reasoning

  • MRCRv2

    Gemini 3.5 Flash77.3%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • MRCR 1M

    Gemini 3.5 Flash26.6%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • ARC-AGI-2

    Gemini 3.5 Flash72.1%
    Source
    Kimi-Audio 7B

    Not directly comparable

Knowledge

  • GPQA-D

    Gemini 3.5 Flash92.7%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • HLE

    Gemini 3.5 Flash40.2%
    Source
    Kimi-Audio 7B

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Gemini 3.5 Flash38.966%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Gemini 3.5 Flash14.583%
    Source
    Kimi-Audio 7B

    Not directly comparable

Multimodal

  • CharXiv

    Gemini 3.5 Flash84.2%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • MMMU-Pro

    Gemini 3.5 Flash83.6%
    Source
    Kimi-Audio 7B

    Not directly comparable

  • Blueprint-Bench 2

    Gemini 3.5 Flash33.6%
    Source
    Kimi-Audio 7B

    Not directly comparable

Frequently asked questions

Which is better, Gemini 3.5 Flash or Kimi-Audio 7B?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Gemini 3.5 Flash or Kimi-Audio 7B?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Gemini 3.5 Flash or Kimi-Audio 7B?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Gemini 3.5 Flash or Kimi-Audio 7B?

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 Kimi-Audio 7B?

A complete documented context-window comparison is not available.

Related comparisons

Last updated August 4, 2026

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