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Kimi K2.6 vs Step 5 Preview

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.

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

Moonshot AI logo
Model A
Kimi K2.6

Moonshot AI

65.77/100

Supported · Public rank #37

90% interval 57.574.0

StepFun logo
Model B
Step 5 Preview

StepFun

Evidence status unavailable

90% interval unavailable

Updated September 21, 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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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

    Step 5 Preview

    Step 5 Preview has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Step 5 Preview

    Step 5 Preview 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

    Step 5 Preview

    Step 5 Preview has the lower estimated token cost for this stated workload. Kimi K2.6 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

    Step 5 Preview

    Step 5 Preview 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

    Step 5 Preview 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

    Step 5 Preview 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.

51.5Kimi K2.6Step 5 Preview

Not comparable · BenchAlign

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.

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
6
Kimi K2.6 only
31
Step 5 Preview only
16
Like-for-like categories
0 / 8

1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign 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.

Multimodal

Directional only
Kimi K2.6
63.9
#26/49
Step 5 Preview
61.2
#28/49
Basis
Provisional lane · 2 vs 2 weighted rows
Reading
Directional only

Agentic

Not comparable
Kimi K2.6
47.6
Supported · #73/154
Step 5 Preview
Not ranked
Basis
BenchAlign lane · 12 vs 11 public rows
Reading
Not comparable

Coding

Not comparable
Kimi K2.6
51.5
Supported · #54/156
Step 5 Preview
Not ranked
Basis
BenchAlign lane · 10 vs 6 public rows
Reading
Not comparable

Reasoning

Not comparable
Kimi K2.6
Not ranked
Step 5 Preview
78.5
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Kimi K2.6
61.5
Supported · #32/186
Step 5 Preview
Not ranked
Basis
BenchAlign lane · 5 vs 2 public rows
Reading
Not comparable

Multilingual

Not comparable
Kimi K2.6
Not ranked
Step 5 Preview
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Kimi K2.6
Not ranked
Step 5 Preview
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Kimi K2.6
71.0
#1/7
Step 5 Preview
Not ranked
Basis
Provisional lane · 4 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

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.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

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
Step 5 Preview
$0.00235
Fits in one request

Step 5 Preview has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Kimi K2.6
$0.0595
Fits in one request
Step 5 Preview
$0.0581
Fits in one request

Step 5 Preview 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 K2.6
$0.249
Fits in one request
Cached input priced at the published list-input rate
Step 5 Preview
$0.057
Fits in one request

Step 5 Preview has the lower modeled cost

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

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 K2.6

Not published

Step 5 Preview

$0.05 per 1M cached input tokens

StepFun pricing and rate limits

Reasoning profile

Kimi K2.6

Reasoning

Step 5 Preview

Reasoning

Weight access

Kimi K2.6

Open Weight

Step 5 Preview

Pending

License

Kimi K2.6

Open Weight

Step 5 Preview

Pending

Release date

Kimi K2.6

2026-04-20

Step 5 Preview

2026-09-20

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 $0.0581. Cache-heavy agent loop: $0.249 vs $0.057.
Context tradeoff
Step 5 Preview has the larger documented window (1M).

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
Step 5 Preview
API / mo$2,775
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 evidence53 rows

Agentic

  • Terminal-Bench 2.0

    Kimi K2.666.7%
    Source
    Step 5 Preview

    Not directly comparable

  • BrowseComp

    Kimi K2.683.2%
    Source
    Step 5 Preview88.7%
    Source

    Step 5 Preview leads this result

  • OSWorld-Verified

    Kimi K2.673.1%
    Source
    Step 5 Preview

    Not directly comparable

  • Toolathlon

    Kimi K2.650%
    Source
    Step 5 Preview

    Not directly comparable

  • MCP Atlas

    Kimi K2.655.9%
    Source
    Step 5 Preview85.6%
    Source

    Step 5 Preview leads this result

  • Claw-Eval

    Kimi K2.662.3%
    Source
    Step 5 Preview

    Not directly comparable

  • DeepSearchQA

    Kimi K2.692.5%
    Source
    Step 5 Preview

    Not directly comparable

  • WideResearch

    Kimi K2.680.8%
    Source
    Step 5 Preview

    Not directly comparable

  • Gert Labs

    Kimi K2.656.82%
    Source
    Step 5 Preview

    Not directly comparable

  • ResearchClawBench

    Kimi K2.618.0%
    Source
    Step 5 Preview

    Not directly comparable

  • OSWorld 2.0

    Kimi K2.64.6%
    Source
    Step 5 Preview

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Kimi K2.653.6%
    Source
    Step 5 Preview

    Not directly comparable

  • Terminal-Bench 2.1

    Kimi K2.6
    Step 5 Preview85.0%
    Source

    Not directly comparable

  • Terminal-Bench 4.0

    Kimi K2.6
    Step 5 Preview33.30%
    Source

    Not directly comparable

  • CyberGym

    Kimi K2.6
    Step 5 Preview84.7%
    Source

    Not directly comparable

  • AutomationBench

    Kimi K2.6
    Step 5 Preview44.0%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Kimi K2.6
    Step 5 Preview74.1%
    Source

    Not directly comparable

  • JobBench

    Kimi K2.6
    Step 5 Preview59.0%
    Source

    Not directly comparable

  • APEX-Agents

    Kimi K2.6
    Step 5 Preview37.8%
    Source

    Not directly comparable

  • DRACO

    Kimi K2.6
    Step 5 Preview83.3%
    Source

    Not directly comparable

  • Agents' Last Exam

    Kimi K2.6
    Step 5 Preview29.5%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Kimi K2.680.2%
    Source
    Step 5 Preview

    Not directly comparable

  • LiveCodeBench v6

    Kimi K2.689.6%
    Source
    Step 5 Preview

    Not directly comparable

  • SWE-bench Pro

    Kimi K2.658.6%
    Source
    Step 5 Preview

    Not directly comparable

  • SWE Multilingual

    Kimi K2.676.7%
    Source
    Step 5 Preview

    Not directly comparable

  • SciCode

    Kimi K2.652.2%
    Source
    Step 5 Preview58.9%
    Source

    Step 5 Preview leads this result

  • Terminal-Bench 2.0

    Kimi K2.666.7%
    Source
    Step 5 Preview

    Not directly comparable

  • Vibe Code Bench

    Kimi K2.637.89%
    Source
    Step 5 Preview

    Not directly comparable

  • cursorBench31

    Kimi K2.647.6%
    Source
    Step 5 Preview

    Not directly comparable

  • LiveCodeBench (Vals)

    Kimi K2.686.8%
    Source
    Step 5 Preview

    Not directly comparable

  • SWE-bench (Vals)

    Kimi K2.676.2%
    Source
    Step 5 Preview

    Not directly comparable

  • DeepSWE

    Kimi K2.6
    Step 5 Preview67.7%
    Source

    Not directly comparable

  • Terminal-Bench 2.1

    Kimi K2.6
    Step 5 Preview85.0%
    Source

    Not directly comparable

  • ProgramBench

    Kimi K2.6
    Step 5 Preview80.5%
    Source

    Not directly comparable

  • sweMarathon

    Kimi K2.6
    Step 5 Preview72.7%
    Source

    Not directly comparable

  • MLS-Bench Lite

    Kimi K2.6
    Step 5 Preview40.5%
    Source

    Not directly comparable

Reasoning

  • CritPt

    Kimi K2.6
    Step 5 Preview20.9%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Kimi K2.679.4%
    Source
    Step 5 Preview76%
    Source

    Kimi K2.6 leads this result

  • MMMU-Pro w/ Python

    Kimi K2.680.1%
    Source
    Step 5 Preview

    Not directly comparable

  • CharXiv

    Kimi K2.680.4%
    Source
    Step 5 Preview

    Not directly comparable

  • MathVision

    Kimi K2.687.4%
    Source
    Step 5 Preview

    Not directly comparable

  • V*

    Kimi K2.696.9%
    Source
    Step 5 Preview

    Not directly comparable

  • OfficeQA Pro

    Kimi K2.6
    Step 5 Preview60.3%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Kimi K2.690.5%
    Source
    Step 5 Preview

    Not directly comparable

  • GPQA-D

    Kimi K2.690.5%
    Source
    Step 5 Preview93.5%
    Source

    Step 5 Preview leads this result

  • HLE

    Kimi K2.634.7%
    Source
    Step 5 Preview46.5%
    Source

    Step 5 Preview leads this result

  • GPQA Diamond (Vals)

    Kimi K2.689.1%
    Source
    Step 5 Preview

    Not directly comparable

  • MMLU-Pro (Vals)

    Kimi K2.687.6%
    Source
    Step 5 Preview

    Not directly comparable

Math

  • AIME26

    Kimi K2.696.4%
    Source
    Step 5 Preview

    Not directly comparable

  • HMMT Feb 2026

    Kimi K2.692.7%
    Source
    Step 5 Preview

    Not directly comparable

  • MMAnswerBench

    Kimi K2.686.0%
    Source
    Step 5 Preview

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Kimi K2.638.966%
    Source
    Step 5 Preview

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Kimi K2.614.580%
    Source
    Step 5 Preview

    Not directly comparable

Questions

Which is better, Kimi K2.6 or Step 5 Preview?

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 K2.6 or Step 5 Preview?

Step 5 Preview is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Kimi K2.6 or Step 5 Preview?

Step 5 Preview is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Kimi K2.6 or Step 5 Preview?

For the stated presets, chat costs $0.00295 on Kimi K2.6 and $0.00235 on Step 5 Preview; repository review costs $0.0595 and $0.0581; the cache-heavy agent loop costs $0.249 and $0.057. Kimi K2.6 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Kimi K2.6 or Step 5 Preview?

Step 5 Preview has the larger documented context window: 1M, compared with 256K.

Related comparisons

Last updated September 21, 2026

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