Capability
59.4/100
field median 58
#74 of 224 ranked models
Qwen3.8-27B
Released Aug 5, 2026 — see all recent releases
Decision reading
Qwen3.8-27B scores 59.4 out of 100 and ranks #74 of 224. This profile shows 27 source-displayable benchmark rows; its strongest eligible category is Agentic at #7. Published weights can be self-hosted, but infrastructure cost varies and is not a comparable API token rate.
Data as of August 22, 2026 · How the score is built
Strongest published evidence
Agentic ranks #7. Particularly useful for coding agents, browser research, and computer-use workflows.
Validate before choosing
27 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.
Decision snapshot
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.
Price
Self-hosted; infrastructure cost varies
input median $1
No comparable first-party hosted token rate
Speed
Not measured
field median 91.5 tok/s
Time to first token not measured
Context
262Ktokens
field median 200,000
Maximum output length is tracked separately
Capability shape
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.
Qwen3.8-27B category percentile values
- Agentic96th percentile
- Coding75th percentile
- ReasoningNot eligible
- Knowledge5th percentile
- MathNot eligible
- MultilingualNot eligible
- Multimodal79th percentile
- Instruction following68th percentile
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#7/137
- Coding#36/141
- ReasoningNot ranked
- Knowledge#57/60
- MathNot ranked
- MultilingualNot ranked
- Multimodal#8/34
- Inst. Following#14/41
Top decileTop quartileMid-fieldNot eligible
How much of this is verified
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.
- Agentic7/7 verified
- Coding5/5 verified
- ReasoningNot measured
- Knowledge4/4 verified
- MathNot measured
- MultilingualNot measured
- Multimodal10/10 verified
- Inst. Following1/1 verified
Verified sourceProvisionalNot measured
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- Not publishedQwen3.8-27B model card
- Context window
- 262KQwen3.8-27B model card
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- Qwen publishes the 27B dense checkpoint and a separate FP8 artifact on Hugging Face under Apache-2.0. LM Studio lists a community GGUF package for local use. Qwen Cloud says a hosted qwen3.8-27b service with a default 1M context window and built-in tools is coming soon, so no current first-party API identifier or token rate is stored.
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing recordQwen3.8-27B model card
- Self-host
- Open weights available; hardware estimate not sourced
- Rate limits
- Not tracked yet
Deployment options
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 parametersCategory score record
Scores 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 #7 of 137Percentile 96thWeight 22%7 benchmarksVerified | 67.1 | #7 of 137 | 96th | 22% | 7 benchmarks | Verified |
| CodingRank #36 of 141Percentile 75thWeight 20%5 benchmarksVerified | 58.2 | #36 of 141 | 75th | 20% | 5 benchmarks | Verified |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeRank #57 of 60Percentile 5thWeight 12%4 benchmarksVerified | 49.0 | #57 of 60 | 5th | 12% | 4 benchmarks | Verified |
| MathWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalRank #8 of 34Percentile 79thWeight 12%10 benchmarksVerified | 79.8 | #8 of 34 | 79th | 12% | 10 benchmarks | Verified |
| Inst. FollowingRank #14 of 41Percentile 68thWeight 5%1 benchmarkVerified | 90.3 | #14 of 41 | 68th | 5% | 1 benchmark | Verified |
Benchmark ledger
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.
Coding5 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-bench Pro | Score61.7% | Versus best verified row Best verified: Claude Mythos 5 · 80.3% | Gap18.6 behind | WeightWeighted 10% | Provider exact |
| Terminal-Bench 2.1Terminal-Bench 2.1 (provider run) | Score73.0% | Versus best verified row Best verified: GLM-5.3 · 88.2% | Gap15.2 behind | WeightDisplay only | Provider exact |
| NL2Repo | Score42.3% | Versus best verified row Best verified: DeepSeek V4 Pro 0813 · 61.5% | Gap19.2 behind | WeightDisplay only | Provider exact |
| deepSwe | Score42.2% | Versus best verified row Best verified: GPT-5.6 Sol · 72.7% | Gap30.5 behind | WeightDisplay only | Provider exact |
| LiveCodeBench v6 | Score90.3% | Versus best verified row Best verified: Sakana Fugu-Ultra · 93.2% | Gap2.9 behind | WeightDisplay only | Provider exact |
Agentic7 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| OSWorld-Verified | Score84.3% | Versus best verified row Best verified: Qwen3.8 Max · 86.1% | Gap1.8 behind | WeightWeighted 34% | Provider exact |
| Terminal-Bench 2.1Terminal-Bench 2.1 (provider run) | Score73.0% | Versus best verified row Best verified: GLM-5.3 · 88.2% | Gap15.2 behind | WeightDisplay only | Provider exact |
| CoWorkBench | Score70.7% | Versus best verified row Best verified: Qwen3.8 Max · 74.8% | Gap4.1 behind | WeightDisplay only | Provider exact |
| JobBench | Score33.4% | Versus best verified row Best verified: Muse Spark 1.1 · 54.7% | Gap21.3 behind | WeightDisplay only | Provider exact |
| Agents' Last Exam | Score42.9% | Versus best verified row Best verified: Qwen3.8 Max · 52.4% | Gap9.5 behind | WeightDisplay only | Provider exact |
| WebArena-VerifiedWebArena-Verified Browser Agent Benchmark | Score64.8% | Versus best verified row Best verified: Muse Spark 1.1 · 69% | Gap4.2 behind | WeightDisplay only | Provider exact |
| AndroidWorld | Score81.9% | Versus best verified row Best verified: Qwen3.8 Max · 85.3% | Gap3.4 behind | WeightDisplay only | Provider exact |
Knowledge4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| HLEHumanity's Last Exam | Score30.8% | Versus best verified row Best verified: Claude Opus 5 · 64.7% | Gap33.9 behind | WeightWeighted 45% | Provider exact |
| GPQAGraduate-Level Google-Proof Q&A | Score89.2% | Versus best verified row Best verified: Sakana Fugu-Ultra · 95.5% | Gap6.3 behind | WeightWeighted 7% | Provider exact |
| GPQA-DGPQA Diamond | Score89.2% | Versus best verified row Best verified: Sakana Fugu-Ultra · 95.5% | Gap6.3 behind | WeightDisplay only | Provider exact |
| HLE w/o toolsHumanity's Last Exam without tools | Score30.8% | Versus best verified row Best verified: Claude Mythos 5 · 59% | Gap28.2 behind | WeightDisplay only | Provider exact |
Multimodal10 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| CharXivCharXiv Reasoning | Score90.2% | Versus best verified row Best verified: Claude Mythos 5 · 93.5% | Gap3.3 behind | WeightWeighted 25% | Provider exact |
| MathVision | Score90.0% | Versus best verified row Best verified: Qwen3.8 Max · 95.2% | Gap5.2 behind | WeightDisplay only | Provider exact |
| MathVision w/ PythonMathVision with Python | Score94.6% | Versus best verified row Best verified: Kimi K3 · 97.8% | Gap3.2 behind | WeightDisplay only | Provider exact |
| BabyVision | Score65.7% | Versus best verified row Best verified: Qwen3.8 Max · 82.0% | Gap16.3 behind | WeightDisplay only | Provider exact |
| BabyVision w/ PythonBabyVision with Python | Score85.6% | Versus best verified row Best verified: Qwen3.8 Max · 91.3% | Gap5.7 behind | WeightDisplay only | Provider exact |
| Vision2Web | Score62.9% | Versus best verified row Best verified: Qwen3.8 Max · 69.0% | Gap6.1 behind | WeightDisplay only | Provider exact |
| CharXiv w/o toolsCharXiv Reasoning without tools | Score83.7% | Versus best verified row Best verified: Claude Mythos 5 · 88.9% | Gap5.2 behind | WeightDisplay only | Provider exact |
| OmniDocBench 1.5 | Score91.1% | Versus best verified row Best verified: Qwen3.8 Max · 92.1% | Gap1 behind | WeightDisplay only | Provider exact |
| RealWorldQA | Score85.9% | Versus best verified row Best verified: Qwen3.8 Max · 88.0% | Gap2.1 behind | WeightDisplay only | Provider exact |
| ERQA | Score65.5% | Versus best verified row Best verified: Qwen3.8 Max · 77.8% | Gap12.3 behind | WeightDisplay only | Provider exact |
Inst. Following1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| IFBenchInstruction Following Benchmark | Score79.5% | Versus best verified row Best verified: MAI-Thinking-1 · 85% | Gap5.5 behind | WeightWeighted 65% | Provider exact |
Lineage
The sequence follows explicit supersedes links. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Apr 21, 2026
Qwen3.6-27BScore 53.5 · Price not listed
Aug 5, 2026 · you are here
Qwen3.8-27BScore 59.4 · Price not listed
Base entry
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
Qwen3.8-27B ranks #74 of 224 on the public leaderboard with a score of 59.44/100. It does not yet have enough sourced coverage for a verified position.
Qwen3.8-27B is a open weight model with a 262K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Qwen publishes the 27B dense checkpoint and a separate FP8 artifact on Hugging Face under Apache-2.0. LM Studio lists a community GGUF package for local use. Qwen Cloud says a hosted qwen3.8-27b service with a default 1M context window and built-in tools is coming soon, so no current first-party API identifier or token rate is stored.
Official exact-value snapshot from Qwen's Qwen3.8-27B model card. We keep Terminal-Bench 2.1 and LiveCodeBench v6 separate from the older weighted lanes, preserve no-Code-Interpreter and Code-Interpreter visual results on separate keys, and leave QwenSWEBench, RecreationBench, ClawEval-MM, and SWE-MM outside the schema instead of forcing them into non-equivalent fields. Qwen reports a dense 27B native vision-language model with a 262,144-token native context window extensible to 1,000,000 tokens.
Its explicit predecessor is Qwen3.6-27B. 27 of 402 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Agentic at #7, while its lowest eligible position is Knowledge at #57. particularly useful for coding agents, browser research, and computer-use workflows.
Radar
Full release historyQwen3.8-27B release history
Qwen3.8-27B released
Alibaba · Model release
Source confirmed
Frequently asked questions
How does Qwen3.8-27B perform overall in AI benchmarks?
Qwen3.8-27B ranks #74 out of 224 models on the public BenchAlign leaderboard, with a score of 59.44/100. Its evidence status is Estimated, and this profile shows 27 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Qwen3.8-27B good for knowledge and understanding?
Qwen3.8-27B ranks #57 out of 60 eligible models for knowledge and understanding, with a public category score of 49/100. 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.
Is Qwen3.8-27B good for coding and programming?
Qwen3.8-27B ranks #36 out of 141 eligible models for coding and programming, with a public category score of 58.2/100. 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.
Is Qwen3.8-27B good for agentic tool use and computer tasks?
Qwen3.8-27B ranks #7 out of 137 eligible models for agentic tool use and computer tasks, with a public category score of 67.1/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Qwen3.8-27B good for multimodal and grounded tasks?
Qwen3.8-27B ranks #8 out of 34 eligible models for multimodal and grounded tasks, with a public category score of 79.8/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Qwen3.8-27B good for instruction following?
Qwen3.8-27B ranks #14 out of 41 eligible models for instruction following, with a public category score of 90.3/100. 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.
Is Qwen3.8-27B open source?
Qwen3.8-27B 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.
Does Qwen3.8-27B have full benchmark coverage on BenchLM?
No. Qwen3.8-27B currently has 43 source-displayable rows across 402 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.
What is the context window size of Qwen3.8-27B?
Qwen3.8-27B has a documented context window of 262K. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.
Last updated August 22, 2026. Runtime fields remain blank until a sourced snapshot exists.
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