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Data

Kimi K2.7 Code vs LongCat-2.5

Updated November 9, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. 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
Moonshot AI logo

Moonshot AI

53.63/100

Estimated · Public rank #80

Conditional range 39.3–68.0

Model B
Meituan logo

Meituan

—

Evidence status unavailable

90% interval unavailable

Shared results
2
Kimi K2.7 Code only
11
LongCat-2.5 only
20
Like-for-like categories
0 / 8
Estimated: Kimi K2.7 Code. 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

    LongCat-2.5

    LongCat-2.5 has the larger documented context window.

    Confidence: documented
  • Chat turn cost

    1K fresh input + 500 output tokens

    LongCat-2.5

    LongCat-2.5 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

    LongCat-2.5

    LongCat-2.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
Show secondary and unsupported calls
  • Repository review cost

    50K fresh input + 3K output tokens

    LongCat-2.5

    LongCat-2.5 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

    LongCat-2.5 is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited
  • Agentic work

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

    Not enough matched evidence

    LongCat-2.5 is not ranked on the public lane for agentic, so no winner is named for agentic.

    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.

42.4Kimi K2.7 Code—LongCat-2.5

Not comparable · BenchAlign v5.8

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

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.

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, reasoning, multimodal, 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.

Agentic

Not comparable
Kimi K2.7 Code
39.7
Supported · #74/132
LongCat-2.5
Not ranked
Basis
BenchAlign v5.8 lane · 4 vs 11 public rows
Reading
Not comparable

Coding

Not comparable
Kimi K2.7 Code
42.4
Supported · #67/158
LongCat-2.5
Not ranked
Basis
BenchAlign v5.8 lane · 7 vs 6 public rows
Reading
Not comparable

Reasoning

Not comparable
Kimi K2.7 Code
48.5
Estimated · #55/157
LongCat-2.5
Not ranked
Basis
BenchAlign v5.8 lane · 0 vs 0 public rows
Reading
Not comparable

Multimodal

Not comparable
Kimi K2.7 Code
Not ranked
LongCat-2.5
Not ranked
Basis
BenchAlign v5.8 lane · 0 vs 4 public rows
Reading
Not comparable

Knowledge

Not comparable
Kimi K2.7 Code
54.6
Estimated · #61/179
LongCat-2.5
Not ranked
Basis
BenchAlign v5.8 lane · 0 vs 1 public rows
Reading
Not comparable

Multilingual

Not comparable
Kimi K2.7 Code
Not ranked
LongCat-2.5
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Kimi K2.7 Code
76.6
#68/157
LongCat-2.5
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Kimi K2.7 Code
54.8
Unranked · 2 rankable rows
LongCat-2.5
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, reasoning, multimodal, 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

Kimi K2.7 Code
$0.00295
Fits in one request
LongCat-2.5
$0.0009
Fits in one request

LongCat-2.5 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Kimi K2.7 Code
$0.0595
Fits in one request
LongCat-2.5
$0.0186
Fits in one request

LongCat-2.5 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Kimi K2.7 Code
$0.097
Fits in one request
LongCat-2.5
$0.0192
Fits in one request

LongCat-2.5 has the lower modeled cost

Costs use the listed standard API rates.

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.

Cached-input rate

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

Kimi K2.7 Code

$0.19 per 1M cached input tokens

LongCat-2.5

$0.006 per 1M cached input tokens

LongCat API Platform pricing

Documented inputs

Kimi K2.7 Code

Not sourced

LongCat-2.5

Not sourced

Documented outputs

Kimi K2.7 Code

Not sourced

LongCat-2.5

Not sourced

Provider availability

Kimi K2.7 Code

Not sourced

LongCat-2.5

Not sourced

Reasoning profile

Kimi K2.7 Code

Reasoning

LongCat-2.5

Hybrid

Weight access

Kimi K2.7 Code

Open Weight

LongCat-2.5

Open Weight

License

Kimi K2.7 Code

Open Weight

LongCat-2.5

Open Weight

Release date

Kimi K2.7 Code

2026-06-12

LongCat-2.5

2026-11-02

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
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost
Repository review: $0.0595 vs $0.0186. Cache-heavy agent loop: $0.097 vs $0.0192.
Context tradeoff
LongCat-2.5 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Kimi K2.7 Code or LongCat-2.5?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Kimi K2.7 Code or LongCat-2.5?

LongCat-2.5 is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Kimi K2.7 Code or LongCat-2.5?

LongCat-2.5 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Kimi K2.7 Code or LongCat-2.5?

For the stated presets, chat costs $0.00295 on Kimi K2.7 Code and $0.0009 on LongCat-2.5; repository review costs $0.0595 and $0.0186; the cache-heavy agent loop costs $0.097 and $0.0192. Costs use the listed standard API rates.

Which has the larger context window, Kimi K2.7 Code or LongCat-2.5?

LongCat-2.5 has the larger documented context window: 1M, compared with 256K.

Self-host vs API cost

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

Kimi K2.7 Code
API / mo$3,713
Self-host / mo$27,962
Break-even500M/day
LongCat-2.5
API / mo$1,125
Self-host / mo$57,606
Break-even3.4B/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 evidence33 rows

Agentic

  • Kimi Claw 24/7

    Kimi K2.7 Code46.9%
    Source
    LongCat-2.5—

    Not directly comparable

  • MCP Atlas

    Kimi K2.7 Code76%
    Source
    LongCat-2.583.1%
    Source

    LongCat-2.5 leads this result

  • MCP Mark Verified

    Kimi K2.7 Code81.1%
    Source
    LongCat-2.5—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Kimi K2.7 Code67.0%
    Source
    LongCat-2.5—

    Not directly comparable

  • Terminal-Bench 2.1

    Kimi K2.7 Code—
    LongCat-2.588.4%
    Source

    Not directly comparable

  • Terminal-Bench 4.0

    Kimi K2.7 Code—
    LongCat-2.538.50%
    Source

    Not directly comparable

  • BrowseComp

    Kimi K2.7 Code—
    LongCat-2.591.9%
    Source

    Not directly comparable

  • AutomationBench

    Kimi K2.7 Code—
    LongCat-2.551.8%
    Source

    Not directly comparable

  • HLE w/ tools

    Kimi K2.7 Code—
    LongCat-2.563.1%
    Source

    Not directly comparable

  • Agents' Last Exam

    Kimi K2.7 Code—
    LongCat-2.538.5%
    Source

    Not directly comparable

  • JobBench

    Kimi K2.7 Code—
    LongCat-2.565.4%
    Source

    Not directly comparable

  • skillsBench

    Kimi K2.7 Code—
    LongCat-2.563.3%
    Source

    Not directly comparable

  • SpreadsheetBench 2

    Kimi K2.7 Code—
    LongCat-2.534.9%
    Source

    Not directly comparable

  • Claw-Eval

    Kimi K2.7 Code—
    LongCat-2.578.3%
    Source

    Not directly comparable

Coding

  • Kimi Code Bench v2

    Kimi K2.7 Code62.0%
    Source
    LongCat-2.5—

    Not directly comparable

  • ProgramBench

    Kimi K2.7 Code53.6%
    Source
    LongCat-2.525.5%
    Source

    Kimi K2.7 Code leads this result

  • MLS-Bench Lite

    Kimi K2.7 Code35.1%
    Source
    LongCat-2.5—

    Not directly comparable

  • CursorBench 3.2

    Kimi K2.7 Code49.7%
    Source
    LongCat-2.5—

    Not directly comparable

  • OpenHarmony Bench

    Kimi K2.7 Code52.1%
    Source
    LongCat-2.5—

    Not directly comparable

  • LiveCodeBench (Vals)

    Kimi K2.7 Code82.1%
    Source
    LongCat-2.5—

    Not directly comparable

  • SWE-bench (Vals)

    Kimi K2.7 Code78.2%
    Source
    LongCat-2.5—

    Not directly comparable

  • Terminal-Bench 2.1

    Kimi K2.7 Code—
    LongCat-2.588.4%
    Source

    Not directly comparable

  • DeepSWE

    Kimi K2.7 Code—
    LongCat-2.564.6%
    Source

    Not directly comparable

  • PaperBench

    Kimi K2.7 Code—
    LongCat-2.582.1%
    Source

    Not directly comparable

  • SWE-Atlas Codebase QnA

    Kimi K2.7 Code—
    LongCat-2.558.3%
    Source

    Not directly comparable

  • NL2Repo

    Kimi K2.7 Code—
    LongCat-2.560.5%
    Source

    Not directly comparable

Multimodal

  • Vision2Web

    Kimi K2.7 Code—
    LongCat-2.578.6%
    Source

    Not directly comparable

  • CharXiv

    Kimi K2.7 Code—
    LongCat-2.590.2%
    Source

    Not directly comparable

  • MathVision w/ Python

    Kimi K2.7 Code—
    LongCat-2.596.5%
    Source

    Not directly comparable

  • Video-MME

    Kimi K2.7 Code—
    LongCat-2.585.2%
    Source

    Not directly comparable

Knowledge

  • FrontierScience

    Kimi K2.7 Code—
    LongCat-2.577%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Kimi K2.7 Code54.035%
    Source
    LongCat-2.5—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Kimi K2.7 Code12.195%
    Source
    LongCat-2.5—

    Not directly comparable

33 public results · 2 shared

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Last updated November 9, 2026