Qwen3.8-27B
Alibaba · Open Weight · rank 39 · bench-align-v5
Self-hostedCanonical idqwen3-8-27b
Access typeOpen Weight
Blended $/1MUnavailable75% input / 25% output
Capability shape
Seven axes from the ranking source. A missing axis is drawn as a gap.
Runtime service evidence
Measured values with the date they were observed. Nothing is inferred from a sibling model or a provider claim.
Time to first token: latency to the first answer chunk (Artificial Analysis, via BenchLM). Reasoning models include thinking time, so values can run to tens or hundreds of seconds.
Evidence key: Observed
| Measurement | Value | Observed | Last good | Evidence |
|---|---|---|---|---|
| Time to first token | 48.5 s | 2026-09-17 | 2026-09-17 | |
| Throughput | 45 tok/s | 2026-09-17 | 2026-09-17 |
Regional or per-endpoint measurements appear only when the API supplies them; none are modelled here.
Endpoint and price matrix
Every published price component, including cache reads and writes.
Self-hosted listingQwen publishes Qwen3.8-27B under Apache-2.0 for self-hosting and has not published a first-party hosted token rate for the exact model. BenchLM represents the open-weight row as self-host/free-per-token before infrastructure costs. Qwen Cloud says hosted access is coming soon, so the pricing row does not inherit Qwen3.8 Max rates.No hosted token rate was published for this model, so its per-token price is unavailable rather than zero.
Workload-aware monthly cost example
10 conversations per day × 8 messages × 22 active days, 1200 input and 400 output tokens per message, no cache. This uses the same calculator as the cost simulator, so an unavailable applicable rate makes the example unavailable too.
Modelled monthly costUnavailableThe applicable input rate is unavailable.
Modelled tokensUnavailable
Open the simulatorChange this workload
Benchmark record
52 matched benchmark rows with their published value, unit, and provenance.
Knowledge
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| GPQA Graduate-Level Google-Proof Q&A | 89.2 | 448 questions | Graduate level | GPQA: A Graduate-Level Google-Proof Q&A Benchmark |
| GPQA-D GPQA Diamond | 89.2 | Graduate-level science questions | Graduate level | Trinity-Large-Thinking: Scaling an Open Source Frontier Agent |
| HLE Humanity's Last Exam | 30.8 | Expert-level questions | Frontier expert level | Humanity's Last Exam |
| Artificial Analysis Intelligence Index Artificial Analysis Intelligence Index | 33.9 | Cross-benchmark intelligence index | Display-only external reference | Artificial Analysis |
| AA-GPQA Diamond Artificial Analysis GPQA Diamond | 90.5 | Graduate-level science questions | Graduate-level science reasoning | Artificial Analysis GPQA Diamond Benchmark Leaderboard |
| AA-HLE Artificial Analysis Humanity's Last Exam | 33.9 | Expert-level questions | Frontier expert reasoning | Artificial Analysis Humanity's Last Exam Benchmark Leaderboard |
| AA-Omniscience Index Artificial Analysis Omniscience Index | -10.0 | Knowledge questions | Broad factual knowledge | AA-Omniscience: Knowledge and Hallucination Benchmark |
| AA-Omniscience Accuracy Artificial Analysis Omniscience Accuracy | 15.6 | Knowledge questions | Broad knowledge | Artificial Analysis model benchmarks |
| AA-Omniscience Hallucination Rate Artificial Analysis Omniscience Hallucination Rate | 30.3 | Knowledge questions | Factuality | Artificial Analysis model benchmarks |
| HLE w/o tools Humanity's Last Exam without tools | 30.8 | Expert-level questions | Frontier expert level | Introducing GPT-5.4 mini and nano |
| GPQA Diamond (Vals) GPQA Diamond, Vals AI run | 88.9 | Graduate-level science questions | Expert reasoning | Vals AI GPQA Diamond, Vals AI run leaderboard |
| MMLU-Pro (Vals) MMLU-Pro, Vals AI run | 84.3 | Academic multiple-choice questions | Broad academic knowledge | Vals AI MMLU-Pro, Vals AI run leaderboard |
Coding
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| Terminal-Bench 2.1 Terminal-Bench 2.1 (provider run) | 73.0 | Terminal-based software-agent tasks | Professional software engineering | DeepSeek V4 Flash 0731 update |
| LiveCodeBench v6 LiveCodeBench v6 | 90.3 | Fresh programming problems | Competitive programming level | LiveCodeBench official repository and release documentation |
| SWE-bench Pro SWE-bench Pro | 61.7 | 1,865 repository problems | Long-horizon professional engineering | SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks? |
| VulcanBench v3 VulcanBench v3 | 82.6 | 23 post-cutoff repository tasks in the v3 report | Professional multi-file software engineering | VulcanBench |
| NL2Repo NL2Repo | 42.3 | Natural language to repository tasks | System-level software comprehension | MiniMax M2.7: Early Echoes of Self-Evolution |
| AA Coding Index Artificial Analysis Coding Index | 68.1 | Cross-benchmark coding index | Display-only external reference | Artificial Analysis model leaderboards |
| AA-SciCode Artificial Analysis SciCode | 46.6 | Scientific coding subproblems | Scientific programming | Artificial Analysis SciCode Benchmark Leaderboard |
| LiveCodeBench (Vals) LiveCodeBench, Vals AI run | 84.0 | Competitive programming problems (easy, medium, hard) | Frontier coding | Vals AI LiveCodeBench, Vals AI run leaderboard |
| SWE-bench (Vals) SWE-bench, Vals AI run | 86.0 | Real repository issues by human time bucket | Frontier coding agents | Vals AI SWE-bench, Vals AI run leaderboard |
| DeepSWE DeepSWE | 42.2 | 113 software engineering tasks across 91 repositories and 5 languages | Long-horizon software engineering | DeepSWE benchmark blog |
Reasoning
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| AA-LCR Artificial Analysis Long Context Reasoning | 82.0 | Long-context reasoning tasks | Long-context reasoning | Artificial Analysis model benchmarks |
| MLCR-AA Medical Long Context Reasoning (MLCR-AA) | 21.7 | Long, fragmented medical-record reasoning | Long-context medical reasoning | Medical Long Context Reasoning (MLCR-AA) |
| CritPt Critical Physics Tasks | 5.4 | Research-level physics questions | Research-level physics reasoning | CritPt Benchmark Leaderboard |
Instruction Following
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| IFBench Instruction Following Benchmark | 79.5 | — | — | BenchLM |
Agentic
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| AA Briefcase Artificial Analysis Briefcase | 1398 | Professional knowledge-work tasks | Professional work | Artificial Analysis Briefcase Benchmark Leaderboard |
| AA EnterpriseOps-Gym Artificial Analysis EnterpriseOps-Gym | 44.2 | Enterprise operations workflows | Enterprise agent operations | Artificial Analysis EnterpriseOps-Gym Benchmark Leaderboard |
| AA Tau3 Banking Artificial Analysis Tau3-Banking | 48.0 | Banking tool-use workflows | Agentic banking workflows | Artificial Analysis Tau3-Banking Benchmark Leaderboard |
| Terminal-Bench 2.1 Terminal-Bench 2.1 (provider run) | 73.0 | Terminal-based software-agent tasks | Professional software engineering | DeepSeek V4 Flash 0731 update |
| GDPval-AA GDPval-AA | 1463 | Agentic real-world work tasks | Professional agentic workflows | DeepSeek-V4 Technical Report |
| GDPval-AA GDPval-AA normalized | 48.2 | Economically valuable tasks | Professional agentic workflows | Artificial Analysis model benchmarks |
| AA Agentic Index Artificial Analysis Agentic Index | 46.5 | Cross-benchmark agentic index | Display-only external reference | Artificial Analysis model leaderboards |
| GDP.pdf Artificial Analysis GDP.pdf | 16.4 | Professional document-production tasks | Professional knowledge work | GDP.pdf Benchmark Leaderboard |
| OSWorld-Verified OSWorld-Verified | 84.3 | 369 real-world computer tasks (361 when eight Google Drive tasks are excluded) | Multi-step desktop and cross-application workflows | OSWorld |
| JobBench JobBench | 33.4 | 130 tasks across 35 occupations | Professional multi-source workflows | JobBench: Aligning Agent Work With Human Will |
| AndroidWorld AndroidWorld | 81.9 | Android app workflows | Complex mobile task completion | GLM-5V-Turbo |
| Agents' Last Exam Agents' Last Exam | 42.9 | Agent tasks | Advanced agentic work | DeepSeek V4 Flash 0731 update |
| CoWorkBench CoWorkBench | 70.7 | Long-horizon professional workflows | Cross-domain professional work | Qwen3.8-Max: A New Bar for Coding and Cowork |
| WebArena-Verified WebArena-Verified Browser Agent Benchmark | 64.8 | 812 verified tasks; separate 258-task Hard subset | Audited stateful browser work | WebArena-Verified: A Fully Audited Benchmark for Web Agents |
| Terminal-Bench 2.1 (Vals) Terminal-Bench 2.1, Vals AI run | 58.4 | Difficult terminal tasks | Frontier agentic | Vals AI Terminal-Bench 2.1, Vals AI run leaderboard |
Multimodal & Grounded
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| AA-MMMU-Pro Artificial Analysis MMMU-Pro | 76.3 | Multimodal academic reasoning | Frontier multimodal | Artificial Analysis MMMU-Pro Benchmark Leaderboard |
| MathVision w/ Python MathVision with Python | 94.6 | Visual mathematics problems with Python | Advanced multimodal mathematics | Kimi K3: Open Frontier Intelligence |
| BabyVision w/ Python BabyVision with Python | 85.6 | Visual perception tasks with Python | Fine-grained visual perception | Kimi K3: Open Frontier Intelligence |
| OmniDocBench 1.5 OmniDocBench 1.5 | 91.1 | Document understanding tasks | Grounded document reasoning | Introducing GPT-5.4 mini and nano |
| RealWorldQA RealWorldQA | 85.9 | Real-world visual question answering | General visual reasoning | Qwen3.6 launch benchmarks |
| MathVision MathVision | 90.0 | Visually grounded math problems | Advanced multimodal mathematics | Qwen3.6 launch benchmarks |
| ERQA ERQA | 65.5 | Evidence-based visual QA | Grounded multimodal reasoning | Qwen3.6 launch benchmarks |
| Vision2Web Vision2Web | 62.9 | Screenshot-to-web tasks | Multimodal web generation | GLM-5V-Turbo |
| CharXiv CharXiv Reasoning | 90.2 | Scientific chart reasoning | Scientific visualization reasoning | CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs |
| CharXiv w/o tools CharXiv Reasoning without tools | 83.7 | Scientific chart reasoning (tool-free) | Scientific visualization reasoning | CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs |
| BabyVision BabyVision | 65.7 | Visual perception tasks | Fine-grained visual perception | Muse Spark 1.1 Evaluation Report |
Lifecycle and limitations log
Lifecycle events the source associates with this model, plus what this profile does not claim.
No lifecycle event references this model.
That is not evidence the model has no lifecycle plan — only that this source published none.
What this profile does not claimValues are reproduced exactly as their sources published them, in the units those sources declared; none are converted, interpolated, or averaged across providers. Any field marked unavailable was attempted and not returned — the attempt timestamp is in each badge. Last attempted fetch for this model’s score: 2026-09-17 17:17 UTC.