Qwen · Open weights
Qwen3.8 Flash
Qwen3.8 Flash is Alibaba's latest fast multimodal model, with a million-token context window for coding, agentic workflows, visual understanding, long documents, codebases, and videos.
- Reasoning
- Tools
- Vision
- Structured output
- Video input
- Input
- Text, Images, Video
- Output
- Text
- Reasoning effort
- none · high
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.14
- Output
- $0.42
- Cache read
- $0.016
- Cache write
- $0.20
Reference prices as published by the model provider. API example
Specifications
- Context window
- 991.8K
- Max output
- 131.1K
Side by side
Qwen3.8 Flash compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Qwen3.8 FlashQwenThis model | DeepSeek V4 Flash 0423DeepSeekRemove | |
|---|---|---|
| Provider | Qwen | DeepSeek |
| Discovery tier | Open weights | Open weights |
| Added | Aug 26, 2026 | Oct 7, 2026 |
| Limits | ||
| Context window | 991.81K | 1.05MBest |
| Max output | 131.07K | — |
| Average output | — | 245 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.14 | $0.14 |
| Output | $0.42 | $0.28Best |
| Cache read | $0.016Best | $0.028 |
| Cache write | $0.20 | — |
| Performance | ||
| Throughput | — | 92.6 tok/s |
| Time to first token | — | 2.5 s |
| Request success (24h) | 96.5% | 98.5%Best |
| Benchmark indexes | ||
| Intelligence Index | — | 18.9 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | No |
| Structured output | Yes | Yes |
| Video input | Yes | No |
| Reasoning effort | none, high | none, low, high, max |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Qwen3.8 Flash
- DeepSeek V4 Flash 0423
Intelligence Index
- Qwen3.8 Flash—
- DeepSeek V4 Flash 042318.9
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- Qwen3.8 Flash: —
- DeepSeek V4 Flash 0423: 41.7%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Qwen3.8 Flash: —
- DeepSeek V4 Flash 0423: 7.8%
GPQA Diamond
Graduate-level science questions
- Qwen3.8 Flash: —
- DeepSeek V4 Flash 0423: 71.6%
IFBench
Following precise output instructions
- Qwen3.8 Flash: —
- DeepSeek V4 Flash 0423: 47.2%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Qwen3.8 Flash: —
- DeepSeek V4 Flash 0423: 34.1%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Qwen3.8 Flash: —
- DeepSeek V4 Flash 0423: 94.4%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Qwen3.8 Flash: —
- DeepSeek V4 Flash 0423: 41.7%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Prompt cache hits
- 96.4%
- About $0.0205 per 1M input tokens with caching
- Request success (24h)
- 96.5%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen/qwen3.8-flash",
"reasoning_effort": "none",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="qwen/qwen3.8-flash",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Qwen
Related models
Other Qwen models, starting with the same family.