Capability
58/100
field median 59.1
#91 of 230 ranked models
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Data as of September 2, 2026 · How the score is built
Multilingual ranks #5. A well-rounded choice across a range of tasks.
38 published rows leave some tracked benchmark slots empty. Agentic is its lowest eligible category at #78.
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
58/100
field median 59.1
#91 of 230 ranked models
Price
$0.60input / $3.60 output
input median $1
blended $2.10
Speed
88tok/s
field median 90 tok/s
First token 38.58 s
Context
128Ktokens
field median 256,000
Reported for this model; direct source link not stored
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
Qwen3.5 397B category percentile values
The dashed outline is median of 6 nearest peers.
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Horizontal: blended price per million tokens, log scale · Vertical: public score
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.
Estimate VRAM from known parametersScores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #78 of 143Percentile 46thWeight 22%13 benchmarksVerified | 48.0 | #78 of 143 | 46th | 22% | 13 benchmarks | Verified |
| CodingRank #59 of 148Percentile 61stWeight 20%3 benchmarksVerified | 54.1 | #59 of 148 | 61st | 20% | 3 benchmarks | Verified |
| ReasoningRank Not rankedWeight 17%2 benchmarksVerified | 65.7 | Not ranked | Not available | 17% | 2 benchmarks | Verified |
| KnowledgeRank #50 of 57Percentile 13thWeight 12%6 benchmarksVerified | 53.5 | #50 of 57 | 13th | 12% | 6 benchmarks | Verified |
| MathRank Not rankedWeight 5%5 benchmarksVerified | 74.3 | Not ranked | Not available | 5% | 5 benchmarks | Verified |
| MultilingualRank #5 of 12Percentile 64thWeight 7%2 benchmarksVerified | 69.7 | #5 of 12 | 64th | 7% | 2 benchmarks | Verified |
| MultimodalRank #21 of 36Percentile 43rdWeight 12%6 benchmarksVerified | 60.9 | #21 of 36 | 43rd | 12% | 6 benchmarks | Verified |
| Inst. FollowingRank #19 of 43Percentile 57thWeight 5%1 benchmarkVerified | 87.4 | #19 of 43 | 57th | 5% | 1 benchmark | Verified |
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-bench VerifiedSoftware Engineering Benchmark Verified | Score76.2% | Versus best verified row Best verified: Claude Opus 5 · 96% | Gap19.8 behind | WeightWeighted 16% | Provider exact |
| SWE-bench Pro | Score50.9% | Versus best verified row Best verified: Claude Fable 5.1 · 81.2% | Gap30.3 behind | WeightWeighted 10% | Provider exact |
| LiveCodeBench v6 | Score83.6% | Versus best verified row Best verified: Sakana Fugu-Ultra · 93.2% | Gap9.6 behind | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.0 | Score52.5% | Versus best verified row Best verified: GPT-5.6 Sol · 91.9% | Gap39.4 behind | WeightWeighted 38% | Provider exact |
| BrowseComp | Score62% | Versus best verified row Best verified: GPT-5.6 Sol · 92.2% | Gap30.2 behind | WeightWeighted 28% | Provider exact |
| Claw-Eval | Score56.8% | Versus best verified row Best verified: Ornith-1.5-397B · 81.4% | Gap24.6 behind | WeightDisplay only | Benchmark exact |
| QwenClawBench | Score51.8% | Versus best verified row Best verified: Qwen3.7 Max · 64.3% | Gap12.5 behind | WeightDisplay only | Provider exact |
| τ³-bench resultsτ³-Bench Tool-Agent-User Evaluation | Score68.4% | Versus best verified row Best verified: Mistral Medium 3.5 128B · 91.4% | Gap23 behind | WeightDisplay only | Provider exact |
| VITA-Bench | Score43.7% | Versus best verified row Best verified: Qwen3.7 Max · 47.9% | Gap4.2 behind | WeightDisplay only | Provider exact |
| DeepPlanning | Score37.6% | Versus best verified row Best verified: Qwen3.7 Plus · 62.3% | Gap24.7 behind | WeightDisplay only | Provider exact |
| Toolathlon | Score36.3% | Versus best verified row Best verified: Muse Spark 1.1 · 75.6% | Gap39.3 behind | WeightDisplay only | Provider exact |
| MCP Atlas | Score46.1% | Versus best verified row Best verified: Muse Spark 1.1 · 88.1% | Gap42 behind | WeightDisplay only | Provider exact |
| MCP-Tasks | Score74.2% | Versus best verified row Best verified: Qwen3.5 397B · 74.2% | GapBest verified | WeightDisplay only | Provider exact |
| WideResearch | Score74.0% | Versus best verified row Best verified: Hy4 preview · 83.9% | Gap9.9 behind | WeightDisplay only | Provider exact |
| Gert LabsGert Labs Composite Game Benchmark | Score46.76% | Versus best verified row Best verified: Claude Opus 4.8 · 72.97% | Gap26.2 behind | WeightDisplay only | Benchmark exact |
| ResearchClawBench | Score14.2% | Versus best verified row Best verified: Claude Opus 4.8 · 21.1% | Gap6.9 behind | WeightDisplay only | Benchmark exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| LongBench v2 | Score63.2% | Versus best verified row Best verified: Qwen3.8 Max · 66.3% | Gap3.1 behind | WeightWeighted 38% | Provider exact |
| AI-Needle | Score68.7% | Versus best verified row Best verified: Qwen3.5 397B · 68.7% | GapBest verified | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| HLEHumanity's Last Exam | Score28.7% | Versus best verified row Best verified: Claude Fable 5.1 · 65% | Gap36.3 behind | WeightWeighted 45% | Provider exact |
| MMLU-ProMassive Multitask Language Understanding Professional | Score87.8% | Versus best verified row Best verified: Qwen3.7 Max · 89.6% | Gap1.8 behind | WeightWeighted 30% | Provider exact |
| GPQAGraduate-Level Google-Proof Q&A | Score88.4% | Versus best verified row Best verified: Sakana Fugu-Ultra · 95.5% | Gap7.1 behind | WeightWeighted 7% | Provider exact |
| SuperGPQASuperGPQA: Scaling LLM Evaluation Across 285 Graduate Disciplines | Score70.4% | Versus best verified row Best verified: Qwen 3.6 Max (preview) · 73.9% | Gap3.5 behind | WeightWeighted 7% | Provider exact |
| MMLU-Redux | Score94.9% | Versus best verified row Best verified: Qwen3.7 Max · 95% | Gap0.1 behind | WeightDisplay only | Provider exact |
| C-Eval | Score93% | Versus best verified row Best verified: Qwen3.6 Plus · 93.3% | Gap0.3 behind | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| AIME26AIME 2026 | Score93.3% | Versus best verified row Best verified: GLM-5.2 · 99.2% | Gap5.9 behind | WeightWeighted 25% | Provider exact |
| HMMT Feb 2026Harvard-MIT Mathematics Tournament February 2026 | Score87.9% | Versus best verified row Best verified: Qwen3.7 Max · 97.1% | Gap9.2 behind | WeightWeighted 25% | Provider exact |
| HMMT Feb 2025Harvard-MIT Mathematics Tournament February 2025 | Score94.8% | Versus best verified row Best verified: Qwen3.6 Plus · 96.7% | Gap1.9 behind | WeightDisplay only | Provider exact |
| HMMT Nov 2025Harvard-MIT Mathematics Tournament November 2025 | Score92.7% | Versus best verified row Best verified: Qwen3.6 Plus · 94.6% | Gap1.9 behind | WeightDisplay only | Provider exact |
| MMAnswerBench | Score80.9% | Versus best verified row Best verified: GLM-5.2 · 91.0% | Gap10.1 behind | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMLU-ProX | Score84.7% | Versus best verified row Best verified: Qwen3.7 Max · 87% | Gap2.3 behind | WeightWeighted 100% | Provider exact |
| NOVA-63 | Score59.1% | Versus best verified row Best verified: Qwen3.5 397B · 59.1% | GapBest verified | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMMU-ProMassive Multi-discipline Multimodal Understanding Pro | Score79% | Versus best verified row Best verified: GPT-5.4 Pro · 94% | Gap15 behind | WeightWeighted 45% | Provider exact |
| CharXivCharXiv Reasoning | Score80.8% | Versus best verified row Best verified: Qwen3.8 Max · 93.5% | Gap12.7 behind | WeightWeighted 25% | Provider exact |
| MathVision | Score88.6% | Versus best verified row Best verified: Qwen3.8 Max · 95.2% | Gap6.6 behind | WeightDisplay only | Provider exact |
| VideoMMMU | Score84.7% | Versus best verified row Best verified: Qwen3.8 Max · 88.7% | Gap4 behind | WeightDisplay only | Provider exact |
| ScreenSpot Pro | Score65.6% | Versus best verified row Best verified: Claude Opus 4.8 · 87.9% | Gap22.3 behind | WeightDisplay only | Provider exact |
| V* | Score95.8% | Versus best verified row Best verified: Kimi K2.6 · 96.9% | Gap1.1 behind | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| IFEvalInstruction-Following Eval | Score92.6% | Versus best verified row Best verified: Qwen3.5-27B · 95% | Gap2.4 behind | WeightWeighted 35% | Provider exact |
The sequence follows explicit supersedes links. A successor's displayed score stays at least 0.1 points above its predecessor; raw benchmark rows do not move. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Feb 16, 2026 · you are here
Qwen3.5 397BScore 58.0 · $0.6 / $3.6
Base entry
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
Qwen3.5 397B ranks #91 of 230 on the public leaderboard with a score of 57.98/100. It does not yet have enough sourced coverage for a verified position.
Qwen3.5 397B is a open weight model with a 128K context window. No explicit reasoning mode is documented in this profile.
Qwen3.5 397B sits in the Qwen3.5 397B family with Qwen3.5 397B (Reasoning). 38 of 416 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Multilingual at #5, while its lowest eligible position is Agentic at #78. a well-rounded choice across a range of tasks.
Qwen3.5 397B ranks #91 out of 230 models on the public BenchAlign leaderboard, with a score of 57.98/100. Its evidence status is Estimated, and this profile shows 38 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Qwen3.5 397B ranks #50 out of 57 eligible models for knowledge and understanding, with a public category score of 53.5/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Qwen3.5 397B ranks #59 out of 148 eligible models for coding and programming, with a public category score of 54.1/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Qwen3.5 397B has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Qwen3.5 397B has source-displayable benchmark coverage for reasoning and logic, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Qwen3.5 397B ranks #78 out of 143 eligible models for agentic tool use and computer tasks, with a public category score of 48/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Qwen3.5 397B ranks #21 out of 36 eligible models for multimodal and grounded tasks, with a public category score of 60.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Qwen3.5 397B ranks #19 out of 43 eligible models for instruction following, with a public category score of 87.4/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Qwen3.5 397B ranks #5 out of 12 eligible models for multilingual tasks, with a public category score of 69.7/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Qwen3.5 397B is an open-weight model from Alibaba. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Qwen3.5 397B belongs to the Qwen3.5 397B family. Related tracked variants include Qwen3.5 397B (Reasoning). A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
No. Qwen3.5 397B currently has 55 source-displayable rows across 416 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
Qwen3.5 397B has a reported context window of 128K in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.
Related resources
Last updated September 2, 2026. Runtime fields remain blank until a sourced snapshot exists.
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