Qwen3 VL 8B Instruct
Qwen · released Oct 14, 2025
Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, images, and video. It features improved multimodal fusion with Interleaved-MRoPE for long-horizon...
Specification
- Context window
- 262K
- Max output
- 33K
- Knowledge cutoff
- Not stated
- Parameters
- 8.8B
- Licence
- apache-2.0
- Serving providers
- 2
- Moderated
- No
- Uptime
- 100.0%
Intelligence
8.2
28th percentile
Coding
—
Coding Index
Agentic
—
Agentic Index
Output speed
51 t/s
Median across providers
Latency
357ms
Time to first token
Cost per task
$0.02
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- MMLU-Pro68.6%
- GPQA Diamond42.7%
- LiveCodeBench33.2%
- IFBench32.3%
- τ²-bench (Telecom)29.2%
- AIME 202527.3%
- SciCode17.4%
- AA-LCR (long context)16.7%
- Humanity's Last Exam2.7%
- Terminal-Bench Hard2.3%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| MMLU-Pro | 68.6% |
| GPQA Diamond | 42.7% |
| LiveCodeBench | 33.2% |
| IFBench | 32.3% |
| τ²-bench (Telecom) | 29.2% |
| AIME 2025 | 27.3% |
| SciCode | 17.4% |
| AA-LCR (long context) | 16.7% |
| Humanity's Last Exam | 2.7% |
| Terminal-Bench Hard | 2.3% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- SonarPerplexity9.4
- Sonar ProPerplexity9.1
- GPT-4o (2024-05-13)OpenAI8.4
- Qwen3 VL 8B InstructQwen8.2
- GPT-4 TurboOpenAI7.7
- Command ACohere7.5
- Nemotron 3 Nano 30B A3BNVIDIA7.2
- Mistral Large 2407Mistral AI7.0
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| Sonar | 9.4 |
| Sonar Pro | 9.1 |
| GPT-4o (2024-05-13) | 8.4 |
| Qwen3 VL 8B Instruct | 8.2 |
| GPT-4 Turbo | 7.7 |
| Command A | 7.5 |
| Nemotron 3 Nano 30B A3B | 7.2 |
| Mistral Large 2407 | 7.0 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $0.117
- Output / 1M tokens
- $0.455
- Cached input / 1M
- Not offered
- Blended 3:1
- $0.202
One task, estimated
$0.02
- Input tokens
- 50,000
- Output tokens
- 25,000
- Profile
- Standard
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).