Long documents
Prompts that approach the documented context limit
Kimi K2.6
Kimi K2.6 has the larger documented context window.
Confidence: documented
Claude Opus 4.5 vs Kimi K2.6
Updated October 10, 2026. Rank says Kimi K2.6 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
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Decision reading
Kimi K2.6 has the higher public point estimate, 58.74 versus 54.14. Their conditional score ranges overlap. These ranges do not establish rank confidence. 23 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 23
- Claude Opus 4.5 only
- 38
- Kimi K2.6 only
- 14
- Like-for-like categories
- 2 / 8
Supported: Claude Opus 4.5 · Estimated: Kimi K2.6. 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 K2.6
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
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-ratesCoding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Claude Opus 4.5 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Claude Opus 4.5 is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limitedCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Claude Opus 4.5 does not fit this workload in one request. Claude Opus 4.5 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
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.
41.2Claude Opus 4.543.9Kimi K2.6
Directional only · BenchAlign v5.8
Kimi K2.6 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.
38 Claude Opus 4.5 only
23 Shared
14 Kimi K2.6 only
3 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.
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.
FrontierMath v2 (Tiers 1-3)Math
Normalized gap 18.3Claude Opus 4.5:20.690%Kimi K2.6:38.966%CharXivMultimodal
Normalized gap 11.9Claude Opus 4.5:68.5%Kimi K2.6:80.4%FrontierMath v2 (Tier 4)Math
Normalized gap 10.4Claude Opus 4.5:4.167%Kimi K2.6:14.580%MMMU-ProMultimodal
Normalized gap 8.8Claude Opus 4.5:70.6%Kimi K2.6:79.4%Terminal-Bench 2.0Agentic
Normalized gap 7.4Claude Opus 4.5:59.3%Kimi K2.6:66.7%
Bars run 0–100 on each benchmark’s normalized display scale
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.
Multimodal
Like-for-like- Claude Opus 4.5
- 48.6
- #49/54
- Kimi K2.6
- 73.8
- #27/54
- Basis
- Provisional lane · 2 vs 2 weighted rows
- Reading
- Kimi K2.6 leads
Math
Like-for-like- Claude Opus 4.5
- 59.0
- #6/7
- Kimi K2.6
- 72.2
- #1/7
- Basis
- Provisional lane · 4 vs 4 weighted rows
- Reading
- Kimi K2.6 leads
Agentic
Directional only- Claude Opus 4.5
- 31.2
- Estimated · #86/123
- Kimi K2.6
- 43.7
- Supported · #57/123
- Basis
- BenchAlign v5.8 lane · 15 vs 12 public rows
- Reading
- Directional only
Coding
Directional only- Claude Opus 4.5
- 41.2
- Estimated · #61/146
- Kimi K2.6
- 43.9
- Supported · #54/146
- Basis
- BenchAlign v5.8 lane · 6 vs 10 public rows
- Reading
- Directional only
Knowledge
Directional only- Claude Opus 4.5
- 51.1
- Estimated · #71/177
- Kimi K2.6
- 59.8
- Supported · #45/177
- Basis
- BenchAlign v5.8 lane · 6 vs 5 public rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Opus 4.5
- 78.4
- Unranked · 4 rankable rows
- Kimi K2.6
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 4.5
- 96.5
- #2/17
- Kimi K2.6
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Opus 4.5
- 31.9
- #115/127
- Kimi K2.6
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Opus 4.5 | Kimi K2.6 | Basis | Reading |
|---|---|---|---|---|
| Multimodal | 48.6#49/54 | 73.8#27/54 | Like-for-likeProvisional lane · 2 vs 2 weighted rows | Kimi K2.6 leads |
| Math | 59.0#6/7 | 72.2#1/7 | Like-for-likeProvisional lane · 4 vs 4 weighted rows | Kimi K2.6 leads |
| Agentic | 31.2Estimated · #86/123 | 43.7Supported · #57/123 | Directional onlyBenchAlign v5.8 lane · 15 vs 12 public rows | Directional only |
| Coding | 41.2Estimated · #61/146 | 43.9Supported · #54/146 | Directional onlyBenchAlign v5.8 lane · 6 vs 10 public rows | Directional only |
| Knowledge | 51.1Estimated · #71/177 | 59.8Supported · #45/177 | Directional onlyBenchAlign v5.8 lane · 6 vs 5 public rows | Directional only |
| Reasoning | 78.4Unranked · 4 rankable rows | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Multilingual | 96.5#2/17 | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Instruction following | 31.9#115/127 | Not ranked | Not comparableProvisional lane · 1 vs 0 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
- Claude Opus 4.5
- $0.0175
- 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 Opus 4.5
- $0.325
- 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 Opus 4.5
- $1.35
- Does not fit in one request
- Cached input priced at the published list-input rate
- Kimi K2.6
- $0.091
- Fits in one request
Claude Opus 4.5 does not fit this workload in one request. Claude Opus 4.5 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.
SpecificationClaude Opus 4.5Kimi K2.6
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 4.5
200K
Kimi K2.6
256K
API model ID
Claude Opus 4.5
Not sourced
Kimi 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 Opus 4.5
Not published
Kimi K2.6
$0.16 per 1M cached input tokens
Documented inputs
Claude Opus 4.5
Not sourced
Kimi K2.6
Not sourced
Documented outputs
Claude Opus 4.5
Not sourced
Kimi K2.6
Not sourced
Provider availability
Claude Opus 4.5
Not sourced
Kimi K2.6
Not sourced
Reasoning profile
Claude Opus 4.5
Non-Reasoning
Kimi K2.6
Reasoning
Weight access
Claude Opus 4.5
Proprietary
Kimi K2.6
Open Weight
License
Claude Opus 4.5
Proprietary
Kimi K2.6
Open Weight
Release date
Claude Opus 4.5
2025-11-01
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
- Kimi K2.6 has the higher public point estimate, 58.74 versus 54.14. Their conditional score ranges overlap. These ranges do not establish rank confidence.
- Workload cost
- Repository review: $0.325 vs $0.0595. Cache-heavy agent loop: $1.35 vs $0.091.
- Context tradeoff
- Kimi K2.6 has the larger documented window (256K).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Claude Opus 4.5 or Kimi K2.6?
Kimi K2.6 has the higher public point estimate, 58.74 versus 54.14. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Claude Opus 4.5 or Kimi K2.6?
Kimi K2.6 scores higher for coding on the public lane, 43.9 to 41.2. Claude Opus 4.5 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, Claude Opus 4.5 or Kimi K2.6?
Kimi K2.6 scores higher for agentic tasks on the public lane, 43.7 to 31.2. Claude Opus 4.5 is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which costs less, Claude Opus 4.5 or Kimi K2.6?
For the stated presets, chat costs $0.0175 on Claude Opus 4.5 and $0.00295 on Kimi K2.6; repository review costs $0.325 and $0.0595; the cache-heavy agent loop costs $1.35 and $0.091. Claude Opus 4.5 does not fit this workload in one request. Claude Opus 4.5 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Claude Opus 4.5 or Kimi K2.6?
Kimi K2.6 has the larger documented context window: 256K, compared with 200K.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Claude Opus 4.5
API / mo$22,500
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 evidence75 rows
Agentic
Terminal-Bench 2.0
Claude Opus 4.559.3%SourceKimi K2.666.7%SourceKimi K2.6 leads this result
OSWorld-Verified
Claude Opus 4.566.3%SourceKimi K2.673.1%SourceKimi K2.6 leads this result
OSWorld
Claude Opus 4.566.3%SourceKimi K2.6—Not directly comparable
Claw-Eval
Claude Opus 4.559.6%SourceKimi K2.662.3%SourceKimi K2.6 leads this result
QwenClawBench
Claude Opus 4.552.3%SourceKimi K2.6—Not directly comparable
τ³-bench results
Claude Opus 4.570.2%SourceKimi K2.6—Not directly comparable
VITA-Bench
Claude Opus 4.523.3%SourceKimi K2.6—Not directly comparable
DeepPlanning
Claude Opus 4.526.4%SourceKimi K2.6—Not directly comparable
Toolathlon
Claude Opus 4.543.5%SourceKimi K2.650%SourceKimi K2.6 leads this result
MCP Atlas
Claude Opus 4.542.3%SourceKimi K2.655.9%SourceKimi K2.6 leads this result
MCP-Tasks
Claude Opus 4.571.8%SourceKimi K2.6—Not directly comparable
WideResearch
Claude Opus 4.576.4%SourceKimi K2.680.8%SourceKimi K2.6 leads this result
CyberGym
Claude Opus 4.550.6%SourceKimi K2.6—Not directly comparable
Gert Labs
Shared sourceClaude Opus 4.564.23%Kimi K2.656.82%Claude Opus 4.5 leads this result
JobBench
Claude Opus 4.532.3%SourceKimi K2.6—Not directly comparable
BrowseComp
Claude Opus 4.5—Kimi K2.683.2%SourceNot directly comparable
DeepSearchQA
Claude Opus 4.5—Kimi K2.692.5%SourceNot directly comparable
ResearchClawBench
Claude Opus 4.5—Kimi K2.618.0%SourceNot directly comparable
OSWorld 2.0
Claude Opus 4.5—Kimi K2.64.6%SourceNot directly comparable
Terminal-Bench 2.1 (Vals)
Claude Opus 4.5—Kimi K2.653.6%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Opus 4.580.9%SourceKimi K2.680.2%SourceClaude Opus 4.5 leads this result
LiveCodeBench v6
Claude Opus 4.584.8%SourceKimi K2.689.6%SourceKimi K2.6 leads this result
SWE-bench Pro
Claude Opus 4.557.1%SourceKimi K2.658.6%SourceKimi K2.6 leads this result
SWE Multilingual
Claude Opus 4.577.5%SourceKimi K2.676.7%SourceClaude Opus 4.5 leads this result
NL2Repo
Claude Opus 4.543.2%SourceKimi K2.6—Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.559.3%SourceKimi K2.666.7%SourceKimi K2.6 leads this result
SciCode
Claude Opus 4.5—Kimi K2.652.2%SourceNot directly comparable
Vibe Code Bench
Claude Opus 4.5—Kimi K2.637.89%SourceNot directly comparable
cursorBench31
Claude Opus 4.5—Kimi K2.647.6%SourceNot directly comparable
LiveCodeBench (Vals)
Claude Opus 4.5—Kimi K2.686.8%SourceNot directly comparable
SWE-bench (Vals)
Claude Opus 4.5—Kimi K2.676.2%SourceNot directly comparable
Reasoning
Multimodal
MMMU
Claude Opus 4.580.7%SourceKimi K2.6—Not directly comparable
MMMU-Pro
Claude Opus 4.570.6%SourceKimi K2.679.4%SourceKimi K2.6 leads this result
RealWorldQA
Claude Opus 4.577.0%SourceKimi K2.6—Not directly comparable
OmniDocBench 1.5
Claude Opus 4.587.7%SourceKimi K2.6—Not directly comparable
Video-MME (with subtitle)
Claude Opus 4.577.6%SourceKimi K2.6—Not directly comparable
Video-MME (w/o subtitle)
Claude Opus 4.581.4%SourceKimi K2.6—Not directly comparable
MathVision
Claude Opus 4.574.3%SourceKimi K2.687.4%SourceKimi K2.6 leads this result
We-Math
Claude Opus 4.570.0%SourceKimi K2.6—Not directly comparable
DynaMath
Claude Opus 4.579.7%SourceKimi K2.6—Not directly comparable
SimpleVQA
Claude Opus 4.565.7%SourceKimi K2.6—Not directly comparable
CharXiv
Claude Opus 4.568.5%SourceKimi K2.680.4%SourceKimi K2.6 leads this result
CountBench
Claude Opus 4.590.6%SourceKimi K2.6—Not directly comparable
AI2D_TEST
Claude Opus 4.587.7%SourceKimi K2.6—Not directly comparable
ERQA
Claude Opus 4.546.8%SourceKimi K2.6—Not directly comparable
VideoMMMU
Claude Opus 4.584.4%SourceKimi K2.6—Not directly comparable
MLVU (M-Avg)
Claude Opus 4.581.7%SourceKimi K2.6—Not directly comparable
ScreenSpot Pro
Claude Opus 4.545.7%SourceKimi K2.6—Not directly comparable
V*
Claude Opus 4.567.0%SourceKimi K2.696.9%SourceKimi K2.6 leads this result
MMMU-Pro w/ Python
Claude Opus 4.5—Kimi K2.680.1%SourceNot directly comparable
Knowledge
GPQA
Claude Opus 4.587%SourceKimi K2.690.5%SourceKimi K2.6 leads this result
SuperGPQA
Claude Opus 4.570.6%SourceKimi K2.6—Not directly comparable
MMLU-Pro
Claude Opus 4.589.5%SourceKimi K2.6—Not directly comparable
MMLU-Redux
Claude Opus 4.596.6%SourceKimi K2.6—Not directly comparable
C-Eval
Claude Opus 4.592.2%SourceKimi K2.6—Not directly comparable
HLE
Claude Opus 4.530.8%SourceKimi K2.634.7%SourceKimi K2.6 leads this result
GPQA-D
Claude Opus 4.5—Kimi K2.690.5%SourceNot directly comparable
GPQA Diamond (Vals)
Claude Opus 4.5—Kimi K2.689.1%SourceNot directly comparable
MMLU-Pro (Vals)
Claude Opus 4.5—Kimi K2.687.6%SourceNot directly comparable
Multilingual
MMLU-ProX
Claude Opus 4.585.7%SourceKimi K2.6—Not directly comparable
NOVA-63
Claude Opus 4.556.7%SourceKimi K2.6—Not directly comparable
INCLUDE
Claude Opus 4.586.2%SourceKimi K2.6—Not directly comparable
PolyMath
Claude Opus 4.579.0%SourceKimi K2.6—Not directly comparable
MAXIFE
Claude Opus 4.579.2%SourceKimi K2.6—Not directly comparable
Instruction following
Math
AIME26
Claude Opus 4.595.1%SourceKimi K2.696.4%SourceKimi K2.6 leads this result
HMMT Feb 2025
Claude Opus 4.592.9%SourceKimi K2.6—Not directly comparable
HMMT Nov 2025
Claude Opus 4.593.3%SourceKimi K2.6—Not directly comparable
HMMT Feb 2026
Claude Opus 4.585.3%SourceKimi K2.692.7%SourceKimi K2.6 leads this result
MMAnswerBench
Claude Opus 4.584.0%SourceKimi K2.686.0%SourceKimi K2.6 leads this result
FrontierMath v2 (Tiers 1-3)
Shared sourceClaude Opus 4.520.690%Kimi K2.638.966%Kimi K2.6 leads this result
FrontierMath v2 (Tier 4)
Shared sourceClaude Opus 4.54.167%Kimi K2.614.580%Kimi K2.6 leads this result
75 public results · 23 shared
Watch Claude Opus 4.5 vs Kimi K2.6
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Last updated October 10, 2026