Agentic
Like-for-like- Claude Sonnet 5
- 81.9
- Kimi K2.6
- 73.5
- Weighted basis
- 3 vs 3 rows
- Reading
- Claude Sonnet 5 leads
Claude Sonnet 5 vs Kimi K2.6
Updated August 14, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Sonnet 5 has the higher public score estimate, 64.78 versus 60.21, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
9 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.
Agentic work
Tool use, computer use, and multi-step task completion
Claude Sonnet 5
Claude Sonnet 5 leads on the same 3 weighted benchmark rows.
Confidence: stronger
Long documents
Prompts that approach the documented context limit
Claude Sonnet 5
Claude Sonnet 5 has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Kimi K2.6
Kimi K2.6 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
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Claude Sonnet 5
Claude Sonnet 5 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
Repository review cost
50K fresh input + 3K output tokens
Kimi K2.6
Kimi K2.6 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
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
10 Claude Sonnet 5 only
9 Shared
23 Kimi K2.6 only
- Shared results
- 9
- Claude Sonnet 5 only
- 10
- Kimi K2.6 only
- 23
- Like-for-like categories
- 1 / 8
3 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
Coding
Directional only- Claude Sonnet 5
- 76.7
- Kimi K2.6
- 64.4
- Weighted basis
- 2 vs 3 rows
- Reading
- Directional only
Knowledge
Directional only- Claude Sonnet 5
- 57.4
- Kimi K2.6
- 42.2
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Multimodal
Directional only- Claude Sonnet 5
- 88.3
- Kimi K2.6
- 79.8
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Sonnet 5
- Not measured
- Kimi K2.6
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Claude Sonnet 5
- Not measured
- Kimi K2.6
- 67.1
- Weighted basis
- 0 vs 4 rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Sonnet 5
- Not measured
- Kimi K2.6
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Sonnet 5
- Not measured
- Kimi K2.6
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Claude Sonnet 5 | Kimi K2.6 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 81.9 | 73.5 | Like-for-like3 vs 3 rows | Claude Sonnet 5 leads |
| Coding | 76.7 | 64.4 | Directional only2 vs 3 rows | Directional only |
| Knowledge | 57.4 | 42.2 | Directional only1 vs 2 rows | Directional only |
| Multimodal | 88.3 | 79.8 | Directional only1 vs 2 rows | Directional only |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Math | Not measured | 67.1 | Not comparable0 vs 4 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | 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.
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.
HLE
Knowledge
Terminal-Bench 2.0
Agentic
OSWorld-Verified
Agentic
CharXiv
Multimodal
SWE-bench Verified
Coding
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
- Claude Sonnet 5
- $0.007
- Fits in one request
- Kimi K2.6
- $0.00295
- Fits in one request
Kimi K2.6 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Sonnet 5
- $0.13
- Fits in one request
- Kimi K2.6
- $0.0595
- Fits in one request
Kimi K2.6 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Sonnet 5
- $0.18
- Fits in one request
- Kimi K2.6
- $0.249
- Fits in one request
- Cached input priced at the published list-input rate
Claude Sonnet 5 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.
SpecificationClaude Sonnet 5Kimi K2.6
Context window
Maximum documented context; output-token limits may be lower.
Claude Sonnet 5
Kimi K2.6
256K
API model ID
Claude Sonnet 5
claude-sonnet-5
Anthropic model overviewKimi K2.6
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Sonnet 5
$0.2 per 1M cached input tokens
Claude API pricingKimi K2.6
Not published
Documented inputs
Claude Sonnet 5
text, image
Anthropic model overviewKimi K2.6
Not sourced
Documented outputs
Claude Sonnet 5
Kimi K2.6
Not sourced
Provider availability
Claude Sonnet 5
Generally Available · Claude API
Anthropic model overviewKimi K2.6
Not sourced
Reasoning profile
Claude Sonnet 5
Reasoning
Kimi K2.6
Reasoning
Weight access
Claude Sonnet 5
Proprietary
Kimi K2.6
Open Weight
License
Claude Sonnet 5
Proprietary
Kimi K2.6
Open Weight
Release date
Claude Sonnet 5
2026-06-30
Kimi K2.6
2026-04-20
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
- Claude Sonnet 5 has the higher public score estimate, 64.78 versus 60.21, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.13 vs $0.0595. Cache-heavy agent loop: $0.18 vs $0.249.
- Context tradeoff
- Claude Sonnet 5 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.
Claude Sonnet 5
API / mo$9,000
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Kimi K2.6
API / mo$3,713
Self-host / mo$18,221
Break-even326M/day
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence42 rows
Agentic
Terminal-Bench 3.0
Claude Sonnet 514.6%SourceKimi K2.6—Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 580.4%SourceKimi K2.666.7%SourceClaude Sonnet 5 leads this result
BrowseComp
Claude Sonnet 584.7%SourceKimi K2.683.2%SourceClaude Sonnet 5 leads this result
HLE w/ tools
Claude Sonnet 557.4%SourceKimi K2.6—Not directly comparable
OSWorld-Verified
Claude Sonnet 581.2%SourceKimi K2.673.1%SourceClaude Sonnet 5 leads this result
Toolathlon
Claude Sonnet 5—Kimi K2.650%SourceNot directly comparable
MCP Atlas
Claude Sonnet 5—Kimi K2.655.9%SourceNot directly comparable
Claw-Eval
Claude Sonnet 5—Kimi K2.662.3%SourceNot directly comparable
DeepSearchQA
Claude Sonnet 5—Kimi K2.692.5%SourceNot directly comparable
WideResearch
Claude Sonnet 5—Kimi K2.680.8%SourceNot directly comparable
Gert Labs
Claude Sonnet 5—Kimi K2.656.82%SourceNot directly comparable
ResearchClawBench
Claude Sonnet 5—Kimi K2.618.0%SourceNot directly comparable
OSWorld 2.0
Claude Sonnet 5—Kimi K2.64.6%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Sonnet 585.2%SourceKimi K2.680.2%SourceClaude Sonnet 5 leads this result
SWE-bench Pro
Claude Sonnet 563.2%SourceKimi K2.658.6%SourceClaude Sonnet 5 leads this result
SWE Multilingual
Claude Sonnet 578.3%SourceKimi K2.676.7%SourceClaude Sonnet 5 leads this result
SWE Multimodal
Claude Sonnet 528.1%SourceKimi K2.6—Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 580.4%SourceKimi K2.666.7%SourceClaude Sonnet 5 leads this result
FrontierCode 1.1 Main
Claude Sonnet 542.7%SourceKimi K2.6—Not directly comparable
cursorBench32
Claude Sonnet 561.5%SourceKimi K2.6—Not directly comparable
APEX-SWE
Claude Sonnet 546.4%SourceKimi K2.6—Not directly comparable
EEBench
Claude Sonnet 540.3%SourceKimi K2.6—Not directly comparable
3DCodeBench
Claude Sonnet 539.2%SourceKimi K2.6—Not directly comparable
LiveCodeBench v6
Claude Sonnet 5—Kimi K2.689.6%SourceNot directly comparable
SciCode
Claude Sonnet 5—Kimi K2.652.2%SourceNot directly comparable
Vibe Code Bench
Claude Sonnet 5—Kimi K2.637.89%SourceNot directly comparable
cursorBench31
Claude Sonnet 5—Kimi K2.647.6%SourceNot directly comparable
Knowledge
Math
AIME26
Claude Sonnet 5—Kimi K2.696.4%SourceNot directly comparable
HMMT Feb 2026
Claude Sonnet 5—Kimi K2.692.7%SourceNot directly comparable
MMAnswerBench
Claude Sonnet 5—Kimi K2.686.0%SourceNot directly comparable
FrontierMath v2 (Tiers 1-3)
Claude Sonnet 5—Kimi K2.638.966%SourceNot directly comparable
FrontierMath v2 (Tier 4)
Claude Sonnet 5—Kimi K2.614.580%SourceNot directly comparable
Multimodal
CharXiv
Claude Sonnet 588.3%SourceKimi K2.680.4%SourceClaude Sonnet 5 leads this result
CharXiv w/o tools
Claude Sonnet 577%SourceKimi K2.6—Not directly comparable
MMMU-Pro
Claude Sonnet 5—Kimi K2.679.4%SourceNot directly comparable
MMMU-Pro w/ Python
Claude Sonnet 5—Kimi K2.680.1%SourceNot directly comparable
MathVision
Claude Sonnet 5—Kimi K2.687.4%SourceNot directly comparable
V*
Claude Sonnet 5—Kimi K2.696.9%SourceNot directly comparable
Frequently asked questions
Which is better, Claude Sonnet 5 or Kimi K2.6?
Claude Sonnet 5 has the higher public score estimate, 64.78 versus 60.21, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Claude Sonnet 5 or Kimi K2.6?
The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, Claude Sonnet 5 or Kimi K2.6?
Claude Sonnet 5 leads the like-for-like agentic tasks comparison across 3 shared weighted benchmark rows.
Which costs less, Claude Sonnet 5 or Kimi K2.6?
For the stated presets, chat costs $0.007 on Claude Sonnet 5 and $0.00295 on Kimi K2.6; repository review costs $0.13 and $0.0595; the cache-heavy agent loop costs $0.18 and $0.249. Kimi K2.6 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Claude Sonnet 5 or Kimi K2.6?
Claude Sonnet 5 has the larger documented context window: 1M, compared with 256K.
Related comparisons
Last updated August 14, 2026
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