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BenchLM
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Gemini 4 Carbon vs Kimi K2.5

Updated October 28, 2026. Rank says Gemini 4 Carbon is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

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 resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Google logo

Google

88.42/100

Estimated · Public rank #1

Conditional range 74.1–100.0

Model B
Moonshot AI logo

Moonshot AI

52.67/100

Supported · Public rank #90

90% interval 43.4–62.0

Shared results
0
Gemini 4 Carbon only
9
Kimi K2.5 only
68
Like-for-like categories
0 / 8
Estimated: Gemini 4 Carbon · Supported: Kimi K2.5. 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.

  • Chat turn cost

    1K fresh input + 500 output tokens

    Kimi K2.5

    Kimi K2.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
  • Cache-heavy agent loop cost

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

    Gemini 4 Carbon

    Gemini 4 Carbon has the lower estimated token cost for this stated workload. Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback
Show secondary and unsupported calls
  • Repository review cost

    50K fresh input + 3K output tokens

    Kimi K2.5

    Kimi K2.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Kimi K2.5 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 4 Carbon 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

    Not enough matched evidence

    A complete context comparison is not sourced.

    Confidence: limited

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.

82.2Gemini 4 Carbon39.6Kimi K2.5

Directional only · BenchAlign v5.8

Gemini 4 Carbon 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 4 Carbon
82.2
Supported · #3/156
Kimi K2.5
39.6
Estimated · #71/156
Basis
BenchAlign v5.8 lane · 1 vs 10 public rows
Reading
Directional only

Knowledge

Directional only
Gemini 4 Carbon
88.2
Supported · #2/178
Kimi K2.5
50.4
Estimated · #78/178
Basis
BenchAlign v5.8 lane · 0 vs 8 public rows
Reading
Directional only

Agentic

Not comparable
Gemini 4 Carbon
Not ranked
Kimi K2.5
42.3
Estimated · #69/134
Basis
BenchAlign v5.8 lane · 4 vs 16 public rows
Reading
Not comparable

Reasoning

Not comparable
Gemini 4 Carbon
79.5
Unranked · 2 rankable rows
Kimi K2.5
71.3
Unranked · 3 rankable rows
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 4 Carbon
Not ranked
Kimi K2.5
70.6
#36/58
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 4 Carbon
Not ranked
Kimi K2.5
87.3
#8/17
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 4 Carbon
Not ranked
Kimi K2.5
85.8
#51/157
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 4 Carbon
Not ranked
Kimi K2.5
83.3
Unranked · 7 rankable rows
Basis
Provisional lane · 0 vs 2 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 4 Carbon
$0.007
Fit state unavailable
Kimi K2.5
$0.0021
Fits in one request

Kimi K2.5 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Gemini 4 Carbon
$0.13
Fit state unavailable
Kimi K2.5
$0.039
Fits in one request

Kimi K2.5 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Gemini 4 Carbon
$0.16
Fit state unavailable
Kimi K2.5
$0.162
Fits in one request
Cached input priced at the published list-input rate

Gemini 4 Carbon has the lower modeled cost

Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input 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.

API model ID

Gemini 4 Carbon

Not sourced

Kimi K2.5

Not sourced

Cached-input rate

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

Gemini 4 Carbon

$0.1 per 1M cached input tokens

Google Gemini 4 Carbon launch post

Kimi K2.5

Not published

Documented inputs

Gemini 4 Carbon

Not sourced

Kimi K2.5

Not sourced

Documented outputs

Gemini 4 Carbon

Not sourced

Kimi K2.5

Not sourced

Reasoning profile

Gemini 4 Carbon

Reasoning

Kimi K2.5

Non-Reasoning

Weight access

Gemini 4 Carbon

Proprietary

Kimi K2.5

Open Weight

License

Gemini 4 Carbon

Proprietary

Kimi K2.5

Open Weight

Release date

Gemini 4 Carbon

2026-10-28

Kimi K2.5

2026-01-27

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
Repository review: $0.13 vs $0.039. Cache-heavy agent loop: $0.16 vs $0.162.
Context tradeoff
A complete documented context comparison is not available.
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Gemini 4 Carbon or Kimi K2.5?

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 4 Carbon or Kimi K2.5?

Gemini 4 Carbon scores higher for coding on the public lane, 82.2 to 39.6. Kimi K2.5 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 4 Carbon or Kimi K2.5?

Gemini 4 Carbon is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Gemini 4 Carbon or Kimi K2.5?

For the stated presets, chat costs $0.007 on Gemini 4 Carbon and $0.0021 on Kimi K2.5; repository review costs $0.13 and $0.039; the cache-heavy agent loop costs $0.16 and $0.162. Kimi K2.5 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Gemini 4 Carbon or Kimi K2.5?

A complete documented context-window comparison is not available.

Self-host vs API cost

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

Gemini 4 Carbon
API / mo$9,000
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Kimi K2.5
API / mo$2,700
Self-host / mo$27,962
Break-even706M/day
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 evidence77 rows

Agentic

  • AutomationBench

    Gemini 4 Carbon53.9%
    Source
    Kimi K2.5—

    Not directly comparable

  • OSWorld 2.1 Offline

    Gemini 4 Carbon81.5%
    Source
    Kimi K2.5—

    Not directly comparable

  • CWE-bench v1

    Gemini 4 Carbon71.0%
    Source
    Kimi K2.5—

    Not directly comparable

  • ExploitGym

    Gemini 4 Carbon53.5%
    Source
    Kimi K2.5—

    Not directly comparable

  • Terminal-Bench 2.0

    Gemini 4 Carbon—
    Kimi K2.550.8%
    Source

    Not directly comparable

  • BrowseComp

    Gemini 4 Carbon—
    Kimi K2.560.6%
    Source

    Not directly comparable

  • OSWorld-Verified

    Gemini 4 Carbon—
    Kimi K2.563.3%
    Source

    Not directly comparable

  • Claw-Eval

    Gemini 4 Carbon—
    Kimi K2.552.3%
    Source

    Not directly comparable

  • QwenClawBench

    Gemini 4 Carbon—
    Kimi K2.554.3%
    Source

    Not directly comparable

  • τ³-bench results

    Gemini 4 Carbon—
    Kimi K2.565.7%
    Source

    Not directly comparable

  • DeepSearchQA

    Gemini 4 Carbon—
    Kimi K2.577.1%
    Source

    Not directly comparable

  • DeepPlanning

    Gemini 4 Carbon—
    Kimi K2.514.4%
    Source

    Not directly comparable

  • Toolathlon

    Gemini 4 Carbon—
    Kimi K2.527.8%
    Source

    Not directly comparable

  • MCP Atlas

    Gemini 4 Carbon—
    Kimi K2.529.5%
    Source

    Not directly comparable

  • MCP-Tasks

    Gemini 4 Carbon—
    Kimi K2.559.1%
    Source

    Not directly comparable

  • WideResearch

    Gemini 4 Carbon—
    Kimi K2.572.7%
    Source

    Not directly comparable

  • BFCL v4

    Gemini 4 Carbon—
    Kimi K2.568.3%
    Source

    Not directly comparable

  • Gert Labs

    Gemini 4 Carbon—
    Kimi K2.545.88%
    Source

    Not directly comparable

  • ResearchClawBench

    Gemini 4 Carbon—
    Kimi K2.514.0%
    Source

    Not directly comparable

  • JobBench

    Gemini 4 Carbon—
    Kimi K2.58.7%
    Source

    Not directly comparable

Coding

  • FrontierSWE v2

    Gemini 4 Carbon61.2%
    Source
    Kimi K2.5—

    Not directly comparable

  • SWE-bench Verified

    Gemini 4 Carbon—
    Kimi K2.576.8%
    Source

    Not directly comparable

  • SWE-bench Verified*

    Gemini 4 Carbon—
    Kimi K2.570.8%
    Source

    Not directly comparable

  • LiveCodeBench v6

    Gemini 4 Carbon—
    Kimi K2.585.0%
    Source

    Not directly comparable

  • SWE-bench Pro

    Gemini 4 Carbon—
    Kimi K2.550.7%
    Source

    Not directly comparable

  • SWE Multilingual

    Gemini 4 Carbon—
    Kimi K2.573%
    Source

    Not directly comparable

  • SWE-Rebench

    Gemini 4 Carbon—
    Kimi K2.558.5%
    Source

    Not directly comparable

  • React Native Evals

    Gemini 4 Carbon—
    Kimi K2.577.2%
    Source

    Not directly comparable

  • NL2Repo

    Gemini 4 Carbon—
    Kimi K2.532%
    Source

    Not directly comparable

  • SciCode

    Gemini 4 Carbon—
    Kimi K2.548.7%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Gemini 4 Carbon—
    Kimi K2.550.8%
    Source

    Not directly comparable

Reasoning

  • GraphWalks BFS 256K–1M

    Gemini 4 Carbon96.2%
    Source
    Kimi K2.5—

    Not directly comparable

  • LongBench v2

    Gemini 4 Carbon—
    Kimi K2.561%
    Source

    Not directly comparable

Multimodal

  • Chartography (no tools)

    Gemini 4 Carbon72.5%
    Source
    Kimi K2.5—

    Not directly comparable

  • Blueprint-Bench 2

    Gemini 4 Carbon58.6%
    Source
    Kimi K2.5—

    Not directly comparable

  • MMMU

    Gemini 4 Carbon—
    Kimi K2.584.3%
    Source

    Not directly comparable

  • MMMU-Pro

    Gemini 4 Carbon—
    Kimi K2.578.5%
    Source

    Not directly comparable

  • RealWorldQA

    Gemini 4 Carbon—
    Kimi K2.581.0%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Gemini 4 Carbon—
    Kimi K2.588.8%
    Source

    Not directly comparable

  • Video-MME

    Gemini 4 Carbon—
    Kimi K2.587.4%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Gemini 4 Carbon—
    Kimi K2.587.4%
    Source

    Not directly comparable

  • Video-MME (w/o subtitle)

    Gemini 4 Carbon—
    Kimi K2.583.2%
    Source

    Not directly comparable

  • MathVision

    Gemini 4 Carbon—
    Kimi K2.584.2%
    Source

    Not directly comparable

  • We-Math

    Gemini 4 Carbon—
    Kimi K2.584.7%
    Source

    Not directly comparable

  • DynaMath

    Gemini 4 Carbon—
    Kimi K2.584.4%
    Source

    Not directly comparable

  • SimpleVQA

    Gemini 4 Carbon—
    Kimi K2.571.2%
    Source

    Not directly comparable

  • MMLongBench-Doc

    Gemini 4 Carbon—
    Kimi K2.558.5%
    Source

    Not directly comparable

  • CC-OCR

    Gemini 4 Carbon—
    Kimi K2.579.7%
    Source

    Not directly comparable

  • AI2D_TEST

    Gemini 4 Carbon—
    Kimi K2.590.8%
    Source

    Not directly comparable

  • CountBench

    Gemini 4 Carbon—
    Kimi K2.594.1%
    Source

    Not directly comparable

  • RefCOCO (avg)

    Gemini 4 Carbon—
    Kimi K2.587.8%
    Source

    Not directly comparable

  • MMVU

    Gemini 4 Carbon—
    Kimi K2.580.4%
    Source

    Not directly comparable

  • VideoMMMU

    Gemini 4 Carbon—
    Kimi K2.586.6%
    Source

    Not directly comparable

  • MLVU (M-Avg)

    Gemini 4 Carbon—
    Kimi K2.585.0%
    Source

    Not directly comparable

  • CharXiv

    Gemini 4 Carbon—
    Kimi K2.577.5%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Gemini 4 Carbon—
    Kimi K2.587.6%
    Source

    Not directly comparable

  • GPQA-D

    Gemini 4 Carbon—
    Kimi K2.587.6%
    Source

    Not directly comparable

  • SuperGPQA

    Gemini 4 Carbon—
    Kimi K2.569.2%
    Source

    Not directly comparable

  • MMLU-Pro

    Gemini 4 Carbon—
    Kimi K2.587.1%
    Source

    Not directly comparable

  • MMLU-Pro (Arcee)

    Gemini 4 Carbon—
    Kimi K2.587.1%
    Source

    Not directly comparable

  • MMLU-Redux

    Gemini 4 Carbon—
    Kimi K2.594.5%
    Source

    Not directly comparable

  • C-Eval

    Gemini 4 Carbon—
    Kimi K2.594%
    Source

    Not directly comparable

  • HLE

    Gemini 4 Carbon—
    Kimi K2.530.1%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    Gemini 4 Carbon—
    Kimi K2.582.3%
    Source

    Not directly comparable

  • NOVA-63

    Gemini 4 Carbon—
    Kimi K2.556.0%
    Source

    Not directly comparable

  • INCLUDE

    Gemini 4 Carbon—
    Kimi K2.583.3%
    Source

    Not directly comparable

  • PolyMath

    Gemini 4 Carbon—
    Kimi K2.543.1%
    Source

    Not directly comparable

  • MAXIFE

    Gemini 4 Carbon—
    Kimi K2.572.8%
    Source

    Not directly comparable

Instruction following

  • Gray Swan IPI (15 attempts)

    Gemini 4 Carbon0.0%
    Source
    Kimi K2.5—

    Not directly comparable

  • IFEval

    Gemini 4 Carbon—
    Kimi K2.593.9%
    Source

    Not directly comparable

Math

  • AIME 2025

    Gemini 4 Carbon—
    Kimi K2.596.1%
    Source

    Not directly comparable

  • AIME26

    Gemini 4 Carbon—
    Kimi K2.595.8%
    Source

    Not directly comparable

  • AIME25 (Arcee)

    Gemini 4 Carbon—
    Kimi K2.596.3%
    Source

    Not directly comparable

  • HMMT Feb 2025

    Gemini 4 Carbon—
    Kimi K2.595.4%
    Source

    Not directly comparable

  • HMMT Nov 2025

    Gemini 4 Carbon—
    Kimi K2.591.1%
    Source

    Not directly comparable

  • HMMT Feb 2026

    Gemini 4 Carbon—
    Kimi K2.587.1%
    Source

    Not directly comparable

  • MMAnswerBench

    Gemini 4 Carbon—
    Kimi K2.581.8%
    Source

    Not directly comparable

77 public results · 0 shared

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Last updated October 28, 2026