Qwen3.8-Omni-Flash
Alibaba · Proprietary · bench-align-v5
Canonical idqwen3-8-omni-flash
Access typeProprietary
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: ObservedUnavailable
| Measurement | Value | Observed | Last good | Evidence |
|---|---|---|---|---|
| Time to first token | Unavailable | Unavailable | Unavailable | |
| Throughput | Unavailable | Unavailable | Unavailable |
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 listingAlibaba Cloud Model Studio's official pricing page lists the hosted qwen3.8-omni-flash SKU at one token rate for every modality. The Chinese mainland and Global deployment tables list CNY 0.8 input, CNY 0.1 cache-hit input, and CNY 2.7 output per million tokens; the Singapore International table lists CNY 1.094 input, CNY 0.117 cache-hit input, and CNY 3.427 output. The USD numeric fields stay null because we do not convert a non-USD first-party price. Qwen's launch post reports the per-hour price of audio input falling by more than 98% and audio-visual input by more than 93% against Qwen3.5-Omni-Plus, which is the direct consequence of dropping the separate audio token rate that the earlier Qwen-Omni SKUs charged.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
19 matched benchmark rows with their published value, unit, and provenance.
Knowledge
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| GPQA Graduate-Level Google-Proof Q&A | 91 | 448 questions | Graduate level | GPQA: A Graduate-Level Google-Proof Q&A Benchmark |
| GPQA-D GPQA Diamond | 91.0 | Graduate-level science questions | Graduate level | Trinity-Large-Thinking: Scaling an Open Source Frontier Agent |
| HLE Humanity's Last Exam | 36.5 | Expert-level questions | Frontier expert level | Humanity's Last Exam |
Coding
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| LiveCodeBench v6 LiveCodeBench v6 | 92.6 | Fresh programming problems | Competitive programming level | LiveCodeBench official repository and release documentation |
| SWE-bench Pro SWE-bench Pro | 63.3 | 1,865 repository problems | Long-horizon professional engineering | SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks? |
| SWE Multilingual SWE Multilingual | 80.5 | Multilingual software-engineering tasks | Professional software engineering | MiniMax M2.7: Early Echoes of Self-Evolution |
| NL2Repo NL2Repo | 48.9 | Natural language to repository tasks | System-level software comprehension | MiniMax M2.7: Early Echoes of Self-Evolution |
| DeepSWE DeepSWE | 57.8 | 113 software engineering tasks across 91 repositories and 5 languages | Long-horizon software engineering | DeepSWE benchmark blog |
Instruction Following
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| IFBench Instruction Following Benchmark | 81.5 | — | — | BenchLM |
Agentic
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| AndroidWorld AndroidWorld | 87.1 | Android app workflows | Complex mobile task completion | GLM-5V-Turbo |
| CoWorkBench CoWorkBench | 75.3 | Long-horizon professional workflows | Cross-domain professional work | Qwen3.8-Max: A New Bar for Coding and Cowork |
Multimodal & Grounded
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| MathVision w/ Python MathVision with Python | 96.2 | Visual mathematics problems with Python | Advanced multimodal mathematics | Kimi K3: Open Frontier Intelligence |
| RealWorldQA RealWorldQA | 87.7 | Real-world visual question answering | General visual reasoning | Qwen3.6 launch benchmarks |
| MathVision MathVision | 91.8 | Visually grounded math problems | Advanced multimodal mathematics | Qwen3.6 launch benchmarks |
| ERQA ERQA | 71.0 | Evidence-based visual QA | Grounded multimodal reasoning | Qwen3.6 launch benchmarks |
| LVBench LVBench | 76.9 | Long-form video question answering | Extended temporal reasoning | Qwen3.8-Max: A New Bar for Coding and Cowork |
| Vision2Web Vision2Web | 62.9 | Screenshot-to-web tasks | Multimodal web generation | GLM-5V-Turbo |
| CharXiv CharXiv Reasoning | 91.4 | Scientific chart reasoning | Scientific visualization reasoning | CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs |
| CharXiv w/o tools CharXiv Reasoning without tools | 83.5 | Scientific chart reasoning (tool-free) | Scientific visualization reasoning | CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs |
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: 2026-09-18 22:17 UTC.