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 55.53. Their conditional score ranges overlap. These ranges do not establish rank confidence. 14 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
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
Qwen3.5 397B
Qwen3.5 397B has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Qwen3.5 397B
Qwen3.5 397B 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
Qwen3.5 397B 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
Qwen3.5 397B is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
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. Qwen3.5 397B 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. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate.
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.
4 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.
HLEKnowledge
Normalized gap 29.2OSWorld-VerifiedAgentic
Normalized gap 21.2SWE-bench ProCoding
Normalized gap 18.3BrowseCompAgentic
Normalized gap 15.3SWE MultilingualCoding
Normalized gap 15.1Each 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 | Qwen3.5 397B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 61.6Supported · #20/123 | 43.8Estimated · #56/123 | Directional onlyBenchAlign v5.8 lane · 12 vs 14 public rows | Directional only |
| Multimodal | 91.2#5/54 | 73.6#29/54 | Directional onlyProvisional lane · 2 vs 2 weighted rows | Directional only |
| Knowledge | 70.7Supported · #14/177 | 53.8Estimated · #63/177 | Directional onlyBenchAlign v5.8 lane · 6 vs 6 public rows | Directional only |
| Instruction following | 75.4#61/127 | 79.9#56/127 | Directional onlyProvisional lane · 0 vs 1 weighted rows | Directional only |
| Coding | 60.8Supported · #19/146 | Not ranked | Not comparableBenchAlign v5.8 lane · 11 vs 6 public rows | Not comparable |
| Reasoning | 62.9#24/28 | 74.9Unranked · 2 rankable rows | Not comparableProvisional lane · 2 vs 1 weighted rows | Not comparable |
| Multilingual | Not ranked | 93.8#5/17 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Math | 65.7#2/7 | 75.0Unranked · 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.
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
Qwen3.5 397B has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Qwen3.5 397B has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Qwen3.5 397B 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. Qwen3.5 397B 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
Qwen3.5 397B
128K
Claude Opus 4.8
claude-opus-4-8
Anthropic model overviewQwen3.5 397B
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
Qwen3.5 397B
Not published
Claude Opus 4.8
text, image
Anthropic model overviewQwen3.5 397B
Not sourced
Claude Opus 4.8
Qwen3.5 397B
Not sourced
Claude Opus 4.8
Generally Available · Claude API
Anthropic model overviewQwen3.5 397B
Not sourced
Claude Opus 4.8
Reasoning
Qwen3.5 397B
Non-Reasoning
Claude Opus 4.8
Proprietary
Qwen3.5 397B
Open Weight
Claude Opus 4.8
Proprietary
Qwen3.5 397B
Open Weight
Claude Opus 4.8
2026-05-28
Qwen3.5 397B
2026-02-16
Claude Opus 4.8 has the higher public point estimate, 69.12 versus 55.53. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Qwen3.5 397B 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 43.8. Qwen3.5 397B 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 $0.0024 on Qwen3.5 397B; repository review costs $0.325 and $0.0408; the cache-heavy agent loop costs $1.35 and $0.168. Qwen3.5 397B 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. Qwen3.5 397B 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 128K.
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
Claude Opus 4.8 leads this result
Toolathlon
Claude Opus 4.8 leads this result
Gert Labs
Shared sourceClaude Opus 4.8 leads this result
ResearchClawBench
Shared sourceClaude Opus 4.8 leads this result
OSWorld 2.0
Not directly comparable
Terminal-Bench 2.1 (Vals)
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
Claw-Eval
Not directly comparable
QwenClawBench
Not directly comparable
τ³-bench results
Not directly comparable
VITA-Bench
Not directly comparable
DeepPlanning
Not directly comparable
MCP-Tasks
Not directly comparable
WideResearch
Not directly comparable
SWE-bench Verified
Claude Opus 4.8 leads this result
SWE-bench Pro
Claude Opus 4.8 leads this result
SWE Multilingual
Claude Opus 4.8 leads this result
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
NL2Repo
Not directly comparable
Terminal-Bench 2.0
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
AI-Needle
Not directly comparable
OfficeQA Pro
Not directly comparable
ScreenSpot Pro
Claude Opus 4.8 leads this result
CharXiv
Claude Opus 4.8 leads this result
CharXiv w/o tools
Not directly comparable
MMMU
Not directly comparable
MMMU-Pro
Not directly comparable
RealWorldQA
Not directly comparable
OmniDocBench 1.5
Not directly comparable
Video-MME (with subtitle)
Not directly comparable
Video-MME (w/o subtitle)
Not directly comparable
MathVision
Not directly comparable
We-Math
Not directly comparable
DynaMath
Not directly comparable
SimpleVQA
Not directly comparable
MMLongBench-Doc
Not directly comparable
CC-OCR
Not directly comparable
AI2D_TEST
Not directly comparable
CountBench
Not directly comparable
RefCOCO (avg)
Not directly comparable
ODINW13
Not directly comparable
ERQA
Not directly comparable
VideoMMMU
Not directly comparable
MLVU (M-Avg)
Not directly comparable
V*
Not directly comparable
GPQA
Claude Opus 4.8 leads this result
GPQA-D
Not directly comparable
HLE
Claude Opus 4.8 leads this result
HLE w/o tools
Not directly comparable
GPQA Diamond (Vals)
Not directly comparable
MMLU-Pro (Vals)
Not directly comparable
SuperGPQA
Not directly comparable
MMLU-Pro
Not directly comparable
MMLU-Redux
Not directly comparable
C-Eval
Not directly comparable
INCLUDE
Claude Opus 4.8 leads this result
MMLU-ProX
Not directly comparable
NOVA-63
Not directly comparable
PolyMath
Not directly comparable
MAXIFE
Not directly comparable
USAMO 2026
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Not directly comparable
FrontierMath v2 (Tier 4)
Not directly comparable
AIME26
Not directly comparable
HMMT Feb 2025
Not directly comparable
HMMT Nov 2025
Not directly comparable
HMMT Feb 2026
Not directly comparable
MMAnswerBench
Not directly comparable
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Last updated October 10, 2026