Long documents
Prompts that approach the documented context limit
Claude Opus 4.8
Claude Opus 4.8 has the larger documented context window.
Confidence: documented
Claude Opus 4.8 vs Kimi K2
Updated October 10, 2026. Rank says Claude Opus 4.8 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
Share or export
Decision reading
Claude Opus 4.8 has the higher public point estimate, 69.12 versus 34.03. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. 6 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 6
- Claude Opus 4.8 only
- 34
- Kimi K2 only
- 9
- Like-for-like categories
- 0 / 8
Supported: Claude Opus 4.8 · Estimated: Kimi K2. 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
Kimi K2 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
Kimi K2 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
Kimi K2 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Kimi K2 is not ranked on the public lane for agentic, so no winner is named for agentic.
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. Kimi K2 does not fit this workload in one request. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. Kimi K2 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.
60.8Claude Opus 4.8—Kimi K2
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.
34 Claude Opus 4.8 only
6 Shared
9 Kimi K2 only
2 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.
HLEKnowledge
Normalized gap 53.2Claude Opus 4.8:57.9%Kimi K2:4.7%SWE MultilingualCoding
Normalized gap 37.1Claude Opus 4.8:84.4%Kimi K2:47.3%FrontierMath v2 (Tier 4)Math
Normalized gap 31.3Claude Opus 4.8:31.250%Kimi K2:0.000%FrontierMath v2 (Tiers 1-3)Math
Normalized gap 25.8Claude Opus 4.8:47.241%Kimi K2:21.404%SWE-bench VerifiedCoding
Normalized gap 22.8Claude Opus 4.8:88.6%Kimi K2:65.8%
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.
Knowledge
Directional only- Claude Opus 4.8
- 70.7
- Supported · #14/177
- Kimi K2
- 36.6
- Estimated · #123/177
- Basis
- BenchAlign v5.8 lane · 6 vs 6 public rows
- Reading
- Directional only
Instruction following
Directional only- Claude Opus 4.8
- 75.4
- #61/127
- Kimi K2
- 48.4
- #85/127
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Directional only
Agentic
Not comparable- Claude Opus 4.8
- 61.6
- Supported · #20/123
- Kimi K2
- Not ranked
- Basis
- BenchAlign v5.8 lane · 12 vs 0 public rows
- Reading
- Not comparable
Coding
Not comparable- Claude Opus 4.8
- 60.8
- Supported · #19/146
- Kimi K2
- Not ranked
- Basis
- BenchAlign v5.8 lane · 11 vs 3 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Opus 4.8
- 62.9
- #24/28
- Kimi K2
- 62.4
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Opus 4.8
- 91.2
- #5/54
- Kimi K2
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 4.8
- Not ranked
- Kimi K2
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Opus 4.8
- 65.7
- #2/7
- Kimi K2
- 39.5
- Unranked · 5 rankable rows
- Basis
- Provisional lane · 3 vs 2 weighted rows
- Reading
- Not comparable
| Category | Claude Opus 4.8 | Kimi K2 | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 70.7Supported · #14/177 | 36.6Estimated · #123/177 | Directional onlyBenchAlign v5.8 lane · 6 vs 6 public rows | Directional only |
| Instruction following | 75.4#61/127 | 48.4#85/127 | Directional onlyProvisional lane · 0 vs 0 weighted rows | Directional only |
| Agentic | 61.6Supported · #20/123 | Not ranked | Not comparableBenchAlign v5.8 lane · 12 vs 0 public rows | Not comparable |
| Coding | 60.8Supported · #19/146 | Not ranked | Not comparableBenchAlign v5.8 lane · 11 vs 3 public rows | Not comparable |
| Reasoning | 62.9#24/28 | 62.4Unranked · 2 rankable rows | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Multimodal | 91.2#5/54 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 65.7#2/7 | 39.5Unranked · 5 rankable rows | Not comparableProvisional lane · 3 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
- Claude Opus 4.8
- $0.0175
- Fits in one request
- Kimi K2
- $0.00185
- Fits in one request
Kimi K2 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Opus 4.8
- $0.325
- Fits in one request
- Kimi K2
- $0.0375
- Fits in one request
Kimi K2 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 4.8
- $1.35
- Fits in one request
- Cached input priced at the published list-input rate
- Kimi K2
- $0.157
- Does not fit in one request
- Cached input priced at the published list-input rate
Kimi K2 does not fit this workload in one request. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. Kimi K2 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 4.8Kimi K2
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 4.8
Kimi K2
128K
API model ID
Claude Opus 4.8
claude-opus-4-8
Anthropic model overviewKimi K2
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 4.8
Not published
Kimi K2
Not published
Documented inputs
Claude Opus 4.8
text, image
Anthropic model overviewKimi K2
Not sourced
Documented outputs
Claude Opus 4.8
Kimi K2
Not sourced
Provider availability
Claude Opus 4.8
Generally Available · Claude API
Anthropic model overviewKimi K2
Not sourced
Reasoning profile
Claude Opus 4.8
Reasoning
Kimi K2
Non-Reasoning
Weight access
Claude Opus 4.8
Proprietary
Kimi K2
Proprietary
License
Claude Opus 4.8
Proprietary
Kimi K2
Proprietary
Release date
Claude Opus 4.8
2026-05-28
Kimi K2
2025-07-01
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 Opus 4.8 has the higher public point estimate, 69.12 versus 34.03. Their conditional score ranges do not overlap. These ranges do not establish rank confidence.
- Workload cost
- Repository review: $0.325 vs $0.0375. Cache-heavy agent loop: $1.35 vs $0.157.
- Context tradeoff
- Claude Opus 4.8 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Claude Opus 4.8 or Kimi K2?
Claude Opus 4.8 has the higher public point estimate, 69.12 versus 34.03. Their conditional score ranges do not 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 4.8 or Kimi K2?
Kimi K2 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Claude Opus 4.8 or Kimi K2?
Kimi K2 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Claude Opus 4.8 or Kimi K2?
For the stated presets, chat costs $0.0175 on Claude Opus 4.8 and $0.00185 on Kimi K2; repository review costs $0.325 and $0.0375; the cache-heavy agent loop costs $1.35 and $0.157. Kimi K2 does not fit this workload in one request. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. Kimi K2 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Claude Opus 4.8 or Kimi K2?
Claude Opus 4.8 has the larger documented context window: 1M, compared with 128K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence49 rows
Agentic
Terminal-Bench 3.0
Claude Opus 4.821.1%SourceKimi K2—Not directly comparable
Terminal-Bench 2.1
Claude Opus 4.874.6%SourceKimi K2—Not directly comparable
BrowseComp
Claude Opus 4.884.3%SourceKimi K2—Not directly comparable
DeepSearchQA
Claude Opus 4.893.1%SourceKimi K2—Not directly comparable
OSWorld-Verified
Claude Opus 4.883.4%SourceKimi K2—Not directly comparable
Finance Agent v2
Claude Opus 4.853.9%SourceKimi K2—Not directly comparable
MCP Atlas
Claude Opus 4.882.2%SourceKimi K2—Not directly comparable
Toolathlon
Claude Opus 4.859.9%SourceKimi K2—Not directly comparable
Gert Labs
Claude Opus 4.872.97%SourceKimi K2—Not directly comparable
ResearchClawBench
Claude Opus 4.821.1%SourceKimi K2—Not directly comparable
OSWorld 2.0
Claude Opus 4.820.6%SourceKimi K2—Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Opus 4.871.9%SourceKimi K2—Not directly comparable
Coding
SWE-bench Verified
Claude Opus 4.888.6%SourceKimi K265.8%SourceClaude Opus 4.8 leads this result
SWE-bench Pro
Claude Opus 4.869.2%SourceKimi K2—Not directly comparable
SWE Multilingual
Claude Opus 4.884.4%SourceKimi K247.3%SourceClaude Opus 4.8 leads this result
SWE Multimodal
Claude Opus 4.838.4%SourceKimi K2—Not directly comparable
Terminal-Bench 2.1
Claude Opus 4.874.6%SourceKimi K2—Not directly comparable
cursorBench31
Claude Opus 4.858.4%SourceKimi K2—Not directly comparable
CursorBench 3.2
Claude Opus 4.862.3%SourceKimi K2—Not directly comparable
FrontierCode 1.1 Main
Claude Opus 4.846.5%SourceKimi K2—Not directly comparable
LiveCodeBench (Vals)
Claude Opus 4.887.8%SourceKimi K2—Not directly comparable
SWE-bench (Vals)
Claude Opus 4.888.6%SourceKimi K2—Not directly comparable
PostTrainBench v1.1
Claude Opus 4.832.9%SourceKimi K2—Not directly comparable
LiveCodeBench v6
Claude Opus 4.8—Kimi K253.7%SourceNot directly comparable
Reasoning
Multimodal
Knowledge
GPQA
Claude Opus 4.893.6%SourceKimi K275.1%SourceClaude Opus 4.8 leads this result
GPQA-D
Claude Opus 4.893.6%SourceKimi K2—Not directly comparable
HLE
Claude Opus 4.857.9%SourceKimi K24.7%SourceClaude Opus 4.8 leads this result
HLE w/o tools
Claude Opus 4.849.8%SourceKimi K2—Not directly comparable
GPQA Diamond (Vals)
Claude Opus 4.892.4%SourceKimi K2—Not directly comparable
MMLU-Pro (Vals)
Claude Opus 4.889.6%SourceKimi K2—Not directly comparable
MMLU
Claude Opus 4.8—Kimi K289.5%SourceNot directly comparable
SuperGPQA
Claude Opus 4.8—Kimi K257.2%SourceNot directly comparable
MMLU-Pro
Claude Opus 4.8—Kimi K281.1%SourceNot directly comparable
SimpleQA
Claude Opus 4.8—Kimi K231%SourceNot directly comparable
Multilingual
INCLUDE
Claude Opus 4.887.6%SourceKimi K2—Not directly comparable
Instruction following
IFEval
Claude Opus 4.8—Kimi K289.8%SourceNot directly comparable
Math
USAMO 2026
Claude Opus 4.896.7%SourceKimi K2—Not directly comparable
FrontierMath v2 (Tiers 1-3)
Shared sourceClaude Opus 4.847.241%Kimi K221.404%Claude Opus 4.8 leads this result
FrontierMath v2 (Tier 4)
Shared sourceClaude Opus 4.831.250%Kimi K20.000%Claude Opus 4.8 leads this result
AIME 2024
Claude Opus 4.8—Kimi K269.6%SourceNot directly comparable
AIME 2025
Claude Opus 4.8—Kimi K249.5%SourceNot directly comparable
MATH-500
Claude Opus 4.8—Kimi K297.4%SourceNot directly comparable
49 public results · 6 shared
Watch Claude Opus 4.8 vs Kimi K2
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 5,500+ readers.
Last updated October 10, 2026