qwen3.8-flash-next
Ultra-efficient multimodal model with elite coding from 6B active parameters.
Value rank
#2 of 12
intelligence per dollar in our catalogue
Context rank
#2 tied
256K token window
Agentic strength
86%
Terminal-Bench v2.1 task completion
Benchmarks
Independent scores by Artificial Analysis, compared with the strongest models in our catalogue.
Intelligence index
Coding index
Agentic (Terminal-Bench v2.1)
Long context
Best for
Where this model earns its keep.
The numbers
Pricing is live from our platform. Prices per 1M tokens, zero data retention on every request.
| Input price | $0.20 |
| Cache read price | $0.05 |
| Output price | $0.50 |
| Context window | 256K tokens |
| Intelligence / coding index | 39.9 / 73.1 |
| Agentic: Terminal-Bench v2.1 / tau2 | 86% / - |
| Long-context reasoning | 80% |
| GPQA / MMLU-Pro | 92% / - |
Or consider
Close alternatives in the catalogue.
deepseek-v4.1-flash
Intelligence 39.5 · agentic -
glm-5.3-flash
Intelligence 41.9 · agentic 84%
deepseek-v4-pro
Intelligence 36.3 · agentic 79%
Quick start
OpenAI-compatible. Switch in one line.
client = OpenAI(base_url="https://api.tensorx.ai/v1", api_key="tsx-...")
r = client.chat.completions.create(
model="qwen/qwen3.8-flash-next",
messages=[{"role": "user", "content": "Hello"}],
)
Benchmark data from the Artificial Analysis Intelligence Index, measured independently. Pricing live from the TensorX platform. All inference on EU-sovereign infrastructure with zero data retention.