Skip to main content
BenchLM
Advertise

Model comparison

Kimi K2.6 vs Mini-Omni 0.5B

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

Kimi K2.6

Moonshot AI

59.0/100

Estimated · Public rank #61

90% interval 49.1–68.9

Mini-Omni 0.5B

gpt-omni

—

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: rate-fallback

  • 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
Kimi K2.6 only
32
Mini-Omni 0.5B 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
Kimi K2.6
73.5
Mini-Omni 0.5B
Not measured
Weighted basis
3 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Kimi K2.6
64.4
Mini-Omni 0.5B
Not measured
Weighted basis
3 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Kimi K2.6
Not measured
Mini-Omni 0.5B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Kimi K2.6
42.2
Mini-Omni 0.5B
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Math

Not comparable
Kimi K2.6
67.1
Mini-Omni 0.5B
Not measured
Weighted basis
4 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Kimi K2.6
Not measured
Mini-Omni 0.5B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Kimi K2.6
79.8
Mini-Omni 0.5B
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Kimi K2.6
Not measured
Mini-Omni 0.5B
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

Kimi K2.6
$0.00295
Fits in one request
Mini-Omni 0.5B
API rate not published
Fit state unavailable

Mini-Omni 0.5B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Kimi K2.6
$0.0595
Fits in one request
Mini-Omni 0.5B
API rate not published
Fit state unavailable

Mini-Omni 0.5B has no comparable published API token rate.

Cache-heavy agent loop

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

Kimi K2.6
$0.249
Fits in one request
Cached input priced at the published list-input rate
Mini-Omni 0.5B
API rate not published
Fit state unavailable
Cached-input rate unavailable

Kimi K2.6 has no published cached-input rate, so cached tokens use its listed input rate. Mini-Omni 0.5B 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.

Kimi K2.6

256K

Mini-Omni 0.5B

N/A

API model ID

Kimi K2.6

Not sourced

Mini-Omni 0.5B

Not sourced

Cached-input rate

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

Kimi K2.6

Not published

Mini-Omni 0.5B

No comparable hosted API rate

gpt-omni model documentation

Documented inputs

Kimi K2.6

Not sourced

Mini-Omni 0.5B

Not sourced

Documented outputs

Kimi K2.6

Not sourced

Mini-Omni 0.5B

Not sourced

Provider availability

Kimi K2.6

Not sourced

Mini-Omni 0.5B

Not sourced

Reasoning profile

Kimi K2.6

Reasoning

Mini-Omni 0.5B

Non-Reasoning

Weight access

Kimi K2.6

Open Weight

Mini-Omni 0.5B

Open Weight

License

Kimi K2.6

Open Weight

Mini-Omni 0.5B

Open Weight

Release date

Kimi K2.6

2026-04-20

Mini-Omni 0.5B

2024-08-29

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.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Kimi K2.6
API / mo$3,713
Self-host / mo$18,221
Break-even326M/day
Mini-Omni 0.5B
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Model the full break-even

Benchmark evidence

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

Browse raw public benchmark evidence32 rows

Agentic

  • Terminal-Bench 2.0

    Kimi K2.666.7%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • BrowseComp

    Kimi K2.683.2%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • OSWorld-Verified

    Kimi K2.673.1%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • Toolathlon

    Kimi K2.650%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • MCP Atlas

    Kimi K2.655.9%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • Claw-Eval

    Kimi K2.662.3%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • DeepSearchQA

    Kimi K2.692.5%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • WideResearch

    Kimi K2.680.8%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • Gert Labs

    Kimi K2.656.82%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • ResearchClawBench

    Kimi K2.618.0%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • OSWorld 2.0

    Kimi K2.64.6%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

Coding

  • SWE-bench Verified

    Kimi K2.680.2%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • LiveCodeBench v6

    Kimi K2.689.6%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • SWE-bench Pro

    Kimi K2.658.6%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • SWE Multilingual

    Kimi K2.676.7%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • SciCode

    Kimi K2.652.2%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • Terminal-Bench 2.0

    Kimi K2.666.7%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • Vibe Code Bench

    Kimi K2.637.89%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • cursorBench31

    Kimi K2.647.6%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

Knowledge

  • GPQA

    Kimi K2.690.5%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • GPQA-D

    Kimi K2.690.5%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • HLE

    Kimi K2.634.7%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

Math

  • AIME26

    Kimi K2.696.4%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • HMMT Feb 2026

    Kimi K2.692.7%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • MMAnswerBench

    Kimi K2.686.0%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Kimi K2.638.966%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Kimi K2.614.580%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

Multimodal

  • MMMU-Pro

    Kimi K2.679.4%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • MMMU-Pro w/ Python

    Kimi K2.680.1%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • CharXiv

    Kimi K2.680.4%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • MathVision

    Kimi K2.687.4%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

  • V*

    Kimi K2.696.9%
    Source
    Mini-Omni 0.5B—

    Not directly comparable

Frequently asked questions

Which is better, Kimi K2.6 or Mini-Omni 0.5B?

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, Kimi K2.6 or Mini-Omni 0.5B?

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, Kimi K2.6 or Mini-Omni 0.5B?

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, Kimi K2.6 or Mini-Omni 0.5B?

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, Kimi K2.6 or Mini-Omni 0.5B?

A complete documented context-window comparison is not available.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 4, 2026

Watch Kimi K2.6 vs Mini-Omni 0.5B

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

Read a sample issue

Join 2,000+ readers.