Long documents
Prompts that approach the documented context limit
Claude Opus 4.8
Claude Opus 4.8 has the larger documented context window.
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
Claude Opus 4.8 has the higher public point estimate, 69.12 versus 56.39. Their conditional score ranges 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.
Moonshot AI
56.39/100
Estimated · Public rank #59
Conditional range 42.0–70.7
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.
Prompts that approach the documented context limit
Claude Opus 4.8
Claude Opus 4.8 has the larger documented context window.
1K fresh input + 500 output tokens
Kimi K2.5 (Reasoning)
Kimi K2.5 (Reasoning) has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Kimi K2.5 (Reasoning)
Kimi K2.5 (Reasoning) has the lower estimated token cost for this stated workload. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. Kimi K2.5 (Reasoning) has no published cached-input rate, so cached tokens use its listed input rate.
50K fresh input + 3K output tokens
Kimi K2.5 (Reasoning)
Kimi K2.5 (Reasoning) has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Kimi K2.5 (Reasoning) is not ranked on the public lane for coding, so no winner is named for coding.
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Kimi K2.5 (Reasoning) is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
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.
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.
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
3 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
BrowseCompAgentic
Normalized gap 23.7OSWorld-VerifiedAgentic
Normalized gap 20.1CharXivMultimodal
Normalized gap 12.4SWE-bench VerifiedCoding
Normalized gap 11.8GPQAKnowledge
Normalized gap 6.0Each 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.
| Category | Claude Opus 4.8 | Kimi K2.5 (Reasoning) | Basis | Reading |
|---|---|---|---|---|
| Agentic | 61.6Supported · #20/123 | 38.2Estimated · #67/123 | Directional onlyBenchAlign v5.8 lane · 12 vs 4 public rows | Directional only |
| Multimodal | 91.2#5/54 | 69.0#33/54 | Directional onlyProvisional lane · 2 vs 2 weighted rows | Directional only |
| Knowledge | 70.7Supported · #14/177 | 49.3Estimated · #80/177 | Directional onlyBenchAlign v5.8 lane · 6 vs 2 public rows | Directional only |
| Coding | 60.8Supported · #19/146 | Not ranked | Not comparableBenchAlign v5.8 lane · 11 vs 4 public rows | Not comparable |
| Reasoning | 62.9#24/28 | 67.1Unranked · 1 rankable row | Not comparableProvisional lane · 2 vs 1 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | 75.4#61/127 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 65.7#2/7 | Not ranked | Not comparableProvisional lane · 3 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.
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.
1K fresh input + 500 output tokens
Kimi K2.5 (Reasoning) has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Kimi K2.5 (Reasoning) has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Kimi K2.5 (Reasoning) has the lower modeled cost
Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. Kimi K2.5 (Reasoning) has no published cached-input rate, so cached tokens use its listed input rate.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Claude Opus 4.8
Kimi K2.5 (Reasoning)
256K
Claude Opus 4.8
claude-opus-4-8
Anthropic model overviewKimi K2.5 (Reasoning)
Not sourced
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 K2.5 (Reasoning)
Not published
Claude Opus 4.8
text, image
Anthropic model overviewKimi K2.5 (Reasoning)
Not sourced
Claude Opus 4.8
Kimi K2.5 (Reasoning)
Not sourced
Claude Opus 4.8
Generally Available · Claude API
Anthropic model overviewKimi K2.5 (Reasoning)
Not sourced
Claude Opus 4.8
Reasoning
Kimi K2.5 (Reasoning)
Reasoning
Claude Opus 4.8
Proprietary
Kimi K2.5 (Reasoning)
Proprietary
Claude Opus 4.8
Proprietary
Kimi K2.5 (Reasoning)
Proprietary
Claude Opus 4.8
2026-05-28
Kimi K2.5 (Reasoning)
2026-02-01
Claude Opus 4.8 has the higher public point estimate, 69.12 versus 56.39. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Kimi K2.5 (Reasoning) is not ranked on the public lane for coding, so no winner is named for coding.
Claude Opus 4.8 scores higher for agentic tasks on the public lane, 61.6 to 38.2. Kimi K2.5 (Reasoning) 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.
For the stated presets, chat costs $0.0175 on Claude Opus 4.8 and $0.0021 on Kimi K2.5 (Reasoning); repository review costs $0.325 and $0.039; the cache-heavy agent loop costs $1.35 and $0.162. Claude Opus 4.8 has no published cached-input rate, so cached tokens use its listed input rate. Kimi K2.5 (Reasoning) has no published cached-input rate, so cached tokens use its listed input rate.
Claude Opus 4.8 has the larger documented context window: 1M, compared with 256K.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 3.0
Not directly comparable
Terminal-Bench 2.1
Not directly comparable
BrowseComp
Claude Opus 4.8 leads this result
DeepSearchQA
Not directly comparable
OSWorld-Verified
Claude Opus 4.8 leads this result
Finance Agent v2
Not directly comparable
MCP Atlas
Not directly comparable
Toolathlon
Not directly comparable
Gert Labs
Shared sourceClaude Opus 4.8 leads this result
ResearchClawBench
Not directly comparable
OSWorld 2.0
Not directly comparable
Terminal-Bench 2.1 (Vals)
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
SWE-bench Verified
Claude Opus 4.8 leads this result
SWE-bench Pro
Not directly comparable
SWE Multilingual
Not directly comparable
SWE Multimodal
Not directly comparable
Terminal-Bench 2.1
Not directly comparable
cursorBench31
Not directly comparable
CursorBench 3.2
Not directly comparable
FrontierCode 1.1 Main
Not directly comparable
LiveCodeBench (Vals)
Not directly comparable
SWE-bench (Vals)
Not directly comparable
PostTrainBench v1.1
Not directly comparable
LiveCodeBench v6
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
Vibe Code Bench
Not directly comparable
ARC-AGI-2
Not directly comparable
ARC-AGI-3
Not directly comparable
ARC-AGI-1
Not directly comparable
LongBench v2
Not directly comparable
OfficeQA Pro
Not directly comparable
ScreenSpot Pro
Not directly comparable
CharXiv
Claude Opus 4.8 leads this result
CharXiv w/o tools
Not directly comparable
MMMU-Pro
Not directly comparable
GPQA
Claude Opus 4.8 leads this result
GPQA-D
Not directly comparable
HLE
Not directly comparable
HLE w/o tools
Not directly comparable
GPQA Diamond (Vals)
Not directly comparable
MMLU-Pro (Vals)
Not directly comparable
MMLU-Pro
Not directly comparable
INCLUDE
Not directly comparable
USAMO 2026
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Not directly comparable
FrontierMath v2 (Tier 4)
Not directly comparable
AIME 2025
Not directly comparable
HMMT Feb 2025
Not directly comparable
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Last updated October 10, 2026