Kimi K3.1 Pro vs Kimi K2.7 Code

Updated October 23, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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. 1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Kimi K3.1 Pro

Moonshot AI

—

Evidence status unavailable

90% interval unavailable

Model B

Kimi K2.7 Code

Moonshot AI

49.26/100

Supported · Public rank #99

90% interval 42.1–56.5

Shared results: 1
Kimi K3.1 Pro only: 41
Kimi K2.7 Code only: 12
Like-for-like categories: 0 / 8

Supported: Kimi K2.7 CodeHow 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
Kimi K3.1 Pro
Kimi K3.1 Pro has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Kimi K2.7 Code
Kimi K2.7 Code 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
Kimi K2.7 Code
Kimi K2.7 Code 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
Kimi K2.7 Code
Kimi K2.7 Code 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 K3.1 Pro 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
Kimi K3.1 Pro 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.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

—Kimi K3.1 Pro41.8Kimi K2.7 Code

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.

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

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.

Agentic

Not comparable

Kimi K3.1 Pro: Not ranked
Kimi K2.7 Code: 38.5; Supported · #73/132
Basis: BenchAlign v5.8 lane · 16 vs 4 public rows
Reading: Not comparable

Coding

Not comparable

Kimi K3.1 Pro: Not ranked
Kimi K2.7 Code: 41.8; Supported · #64/153
Basis: BenchAlign v5.8 lane · 6 vs 7 public rows
Reading: Not comparable

Reasoning

Not comparable

Kimi K3.1 Pro: Not ranked
Kimi K2.7 Code: 79.5; Unranked · 2 rankable rows
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Kimi K3.1 Pro: 98.0; #1/56
Kimi K2.7 Code: Not ranked
Basis: Provisional lane · 3 vs 0 weighted rows
Reading: Not comparable

Knowledge

Not comparable

Kimi K3.1 Pro: Not ranked
Kimi K2.7 Code: 53.6; Estimated · #66/187
Basis: BenchAlign v5.8 lane · 5 vs 0 public rows
Reading: Not comparable

Multilingual

Not comparable

Kimi K3.1 Pro: Not ranked
Kimi K2.7 Code: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Kimi K3.1 Pro: Not ranked
Kimi K2.7 Code: 76.6; #66/153
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

Kimi K3.1 Pro: Not ranked
Kimi K2.7 Code: 58.3; Unranked · 2 rankable rows
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Kimi K3.1 Pro and Kimi K2.7 Code
Category	Kimi K3.1 Pro	Kimi K2.7 Code	Basis	Reading
Agentic	Not ranked	38.5Supported · #73/132	Not comparableBenchAlign v5.8 lane · 16 vs 4 public rows	Not comparable
Coding	Not ranked	41.8Supported · #64/153	Not comparableBenchAlign v5.8 lane · 6 vs 7 public rows	Not comparable
Reasoning	Not ranked	79.5Unranked · 2 rankable rows	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Multimodal	98.0#1/56	Not ranked	Not comparableProvisional lane · 3 vs 0 weighted rows	Not comparable
Knowledge	Not ranked	53.6Estimated · #66/187	Not comparableBenchAlign v5.8 lane · 5 vs 0 public rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Instruction following	Not ranked	76.6#66/153	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Math	Not ranked	58.3Unranked · 2 rankable rows	Not comparableProvisional lane · 0 vs 2 weighted rows	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

Kimi K3.1 Pro: $0.007; Fits in one request
Kimi K2.7 Code: $0.00295; Fits in one request

Kimi K2.7 Code has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Kimi K3.1 Pro: $0.13; Fits in one request
Kimi K2.7 Code: $0.0595; Fits in one request

Kimi K2.7 Code 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 K3.1 Pro: $0.18; Fits in one request
Kimi K2.7 Code: $0.097; Fits in one request

Kimi K2.7 Code 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.

SpecificationKimi K3.1 ProKimi K2.7 Code

Context window

Maximum documented context; output-token limits may be lower.

Kimi K3.1 Pro

1.05M

Kimi K2.7 Code

256K

API model ID

Kimi K3.1 Pro

Not sourced

Kimi K2.7 Code

Not sourced

Cached-input rate

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

Kimi K3.1 Pro

$0.2 per 1M cached input tokens

Kimi K2.7 Code

$0.19 per 1M cached input tokens

Documented inputs

Kimi K3.1 Pro

Not sourced

Kimi K2.7 Code

Not sourced

Documented outputs

Kimi K3.1 Pro

Not sourced

Kimi K2.7 Code

Not sourced

Provider availability

Kimi K3.1 Pro

Not sourced

Kimi K2.7 Code

Not sourced

Reasoning profile

Kimi K3.1 Pro

Reasoning

Kimi K2.7 Code

Reasoning

Weight access

Kimi K3.1 Pro

Pending

Kimi K2.7 Code

Open Weight

License

Kimi K3.1 Pro

Pending

Kimi K2.7 Code

Open Weight

Release date

Kimi K3.1 Pro

2026-10-23

Kimi K2.7 Code

2026-06-12

If you already use one of these models

Deployment change: Both entries list Moonshot AI as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
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: $0.13 vs $0.0595. Cache-heavy agent loop: $0.18 vs $0.097.
Context tradeoff: Kimi K3.1 Pro has the larger documented window (1.05M).

Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Kimi K3.1 Pro or Kimi K2.7 Code?

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 K3.1 Pro or Kimi K2.7 Code?

Kimi K3.1 Pro is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Kimi K3.1 Pro or Kimi K2.7 Code?

Kimi K3.1 Pro is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Kimi K3.1 Pro or Kimi K2.7 Code?

For the stated presets, chat costs $0.007 on Kimi K3.1 Pro and $0.00295 on Kimi K2.7 Code; repository review costs $0.13 and $0.0595; the cache-heavy agent loop costs $0.18 and $0.097. Costs use the listed standard API rates.

Which has the larger context window, Kimi K3.1 Pro or Kimi K2.7 Code?

Kimi K3.1 Pro has the larger documented context window: 1.05M, compared with 256K.

Self-host vs API cost

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

Kimi K3.1 Pro

API / mo$9,000

Self-host / moNot listed

Break-even—

Proprietary model — self-hosting not applicable.

Kimi K2.7 Code

API / mo$3,713

Self-host / mo$27,962

Break-even500M/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 evidence54 rows

Agentic

Terminal-Bench 4.0
Kimi K3.1 Pro65.70%
Source
Kimi K2.7 Code—
Not directly comparable
Terminal-Bench-Science 0.1
Kimi K3.1 Pro38.1%
Source
Kimi K2.7 Code—
Not directly comparable
HLE w/ tools
Kimi K3.1 Pro70.0%
Source
Kimi K2.7 Code—
Not directly comparable
BrowseComp
Kimi K3.1 Pro92.1%
Source
Kimi K2.7 Code—
Not directly comparable
BioMysteryBench
Kimi K3.1 Pro80.6%
Source
Kimi K2.7 Code—
Not directly comparable
Agents' Last Exam
Kimi K3.1 Pro43.2%
Source
Kimi K2.7 Code—
Not directly comparable
Agents' Last Exam (CLI)
Kimi K3.1 Pro44.2%
Source
Kimi K2.7 Code—
Not directly comparable
APEX-Agents
Kimi K3.1 Pro67.2%
Source
Kimi K2.7 Code—
Not directly comparable
Frontier Finance
Kimi K3.1 Pro58.6%
Source
Kimi K2.7 Code—
Not directly comparable
HANDBOOK.md
Kimi K3.1 Pro44.6%
Source
Kimi K2.7 Code—
Not directly comparable
OSWorld 2.0
Kimi K3.1 Pro79.6%
Source
Kimi K2.7 Code—
Not directly comparable
Business Operation
Kimi K3.1 Pro37.8%
Source
Kimi K2.7 Code—
Not directly comparable
Financial Modeling
Kimi K3.1 Pro57.6%
Source
Kimi K2.7 Code—
Not directly comparable
Financial Research
Kimi K3.1 Pro70.4%
Source
Kimi K2.7 Code—
Not directly comparable
Kimi Hallu Bench Hard (tools)
Kimi K3.1 Pro8.3%
Source
Kimi K2.7 Code—
Not directly comparable
ExploitGym
Kimi K3.1 Pro20.7%
Source
Kimi K2.7 Code—
Not directly comparable
Kimi Claw 24/7
Kimi K3.1 Pro—
Kimi K2.7 Code46.9%
Source
Not directly comparable
MCP Atlas
Kimi K3.1 Pro—
Kimi K2.7 Code76%
Source
Not directly comparable
MCP Mark Verified
Kimi K3.1 Pro—
Kimi K2.7 Code81.1%
Source
Not directly comparable
Terminal-Bench 2.1 (Vals)
Kimi K3.1 Pro—
Kimi K2.7 Code67.0%
Source
Not directly comparable

Coding

DeepSWE
Kimi K3.1 Pro75.5%
Source
Kimi K2.7 Code—
Not directly comparable
ProgramBench (binary)
Kimi K3.1 Pro31.5%
Source
Kimi K2.7 Code—
Not directly comparable
Kimi Code Bench v2
Kimi K3.1 Pro77.1%
Source
Kimi K2.7 Code62.0%
Source
Kimi K3.1 Pro leads this result
Kimi Code Bench 3.0 Long-horizon
Kimi K3.1 Pro61.2%
Source
Kimi K2.7 Code—
Not directly comparable
sweMarathon
Kimi K3.1 Pro51.7%
Source
Kimi K2.7 Code—
Not directly comparable
PostTrainBench v1.2
Kimi K3.1 Pro36.5%
Source
Kimi K2.7 Code—
Not directly comparable
ProgramBench
Kimi K3.1 Pro—
Kimi K2.7 Code53.6%
Source
Not directly comparable
MLS-Bench Lite
Kimi K3.1 Pro—
Kimi K2.7 Code35.1%
Source
Not directly comparable
CursorBench 3.2
Kimi K3.1 Pro—
Kimi K2.7 Code49.7%
Source
Not directly comparable
OpenHarmony Bench
Kimi K3.1 Pro—
Kimi K2.7 Code52.1%
Source
Not directly comparable
LiveCodeBench (Vals)
Kimi K3.1 Pro—
Kimi K2.7 Code82.1%
Source
Not directly comparable
SWE-bench (Vals)
Kimi K3.1 Pro—
Kimi K2.7 Code78.2%
Source
Not directly comparable

Multimodal

OfficeQA Pro
Kimi K3.1 Pro67.4%
Source
Kimi K2.7 Code—
Not directly comparable
OfficeQA Pro v2
Kimi K3.1 Pro64.4%
Source
Kimi K2.7 Code—
Not directly comparable
BenchCAD Vision2Code (no tools)
Kimi K3.1 Pro0.728
Source
Kimi K2.7 Code—
Not directly comparable
BenchCAD Vision2Code (tools)
Kimi K3.1 Pro0.927
Source
Kimi K2.7 Code—
Not directly comparable
MMMU-Pro
Kimi K3.1 Pro84.1%
Source
Kimi K2.7 Code—
Not directly comparable
MMMU-Pro w/ Python
Kimi K3.1 Pro90%
Source
Kimi K2.7 Code—
Not directly comparable
CharXiv
Kimi K3.1 Pro93.4%
Source
Kimi K2.7 Code—
Not directly comparable
CharXiv w/o tools
Kimi K3.1 Pro89%
Source
Kimi K2.7 Code—
Not directly comparable
Chartography (tools)
Kimi K3.1 Pro90.2%
Source
Kimi K2.7 Code—
Not directly comparable
BabyVision w/ Python
Kimi K3.1 Pro95.4%
Source
Kimi K2.7 Code—
Not directly comparable
ZeroBench
Kimi K3.1 Pro39.0%
Source
Kimi K2.7 Code—
Not directly comparable
ZeroBench w/ Python
Kimi K3.1 Pro63.0%
Source
Kimi K2.7 Code—
Not directly comparable
GDP.pdf (Gemini judge)
Kimi K3.1 Pro34.6%
Source
Kimi K2.7 Code—
Not directly comparable
GDP.pdf w/ Python (Gemini judge)
Kimi K3.1 Pro85.7%
Source
Kimi K2.7 Code—
Not directly comparable
PerceptionBench
Kimi K3.1 Pro68.3%
Source
Kimi K2.7 Code—
Not directly comparable

Knowledge

GPQA
Kimi K3.1 Pro94.2%
Source
Kimi K2.7 Code—
Not directly comparable
GPQA-D
Kimi K3.1 Pro94.2%
Source
Kimi K2.7 Code—
Not directly comparable
HLE
Kimi K3.1 Pro70%
Source
Kimi K2.7 Code—
Not directly comparable
HLE w/o tools
Kimi K3.1 Pro51.1%
Source
Kimi K2.7 Code—
Not directly comparable
Kimi Hallu Bench
Kimi K3.1 Pro5.4%
Source
Kimi K2.7 Code—
Not directly comparable

Math

FrontierMath v2 (Tiers 1-3)
Kimi K3.1 Pro—
Kimi K2.7 Code54.035%
Source
Not directly comparable
FrontierMath v2 (Tier 4)
Kimi K3.1 Pro—
Kimi K2.7 Code12.195%
Source
Not directly comparable

54 public results · 1 shared

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Last updated October 23, 2026

Kimi K3.1 Pro vs Kimi K2.7 Code

Decision reading

Which one for your work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Coding work

Agentic work

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

Which is better, Kimi K3.1 Pro or Kimi K2.7 Code?

Which is better for coding, Kimi K3.1 Pro or Kimi K2.7 Code?

Which is better for agentic tasks, Kimi K3.1 Pro or Kimi K2.7 Code?

Which costs less, Kimi K3.1 Pro or Kimi K2.7 Code?

Which has the larger context window, Kimi K3.1 Pro or Kimi K2.7 Code?

Self-host vs API cost

Benchmark evidence

Agentic

Coding

Multimodal

Knowledge

Math

Related comparisons

Watch Kimi K3.1 Pro vs Kimi K2.7 Code