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DeepSeek V3.1 vs Qwen3.5 397B A17B

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for DeepSeek V3.1 and Qwen3.5 397B A17B.

DeepSeek

DeepSeek V3.1

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

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Alibaba

Qwen3.5 397B A17B

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...

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Technical Specifications

SpecificationDeepSeek V3.1Qwen3.5 397B A17B
ProviderDeepSeekAlibaba
Context Window163,840 tokens256,000 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelself hostableself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-08-212026-02-16

API Pricing Comparison

Input Price per Million Tokens

DeepSeek V3.1

$0.21

Qwen3.5 397B A17B

$0.39

Output Price per Million Tokens

DeepSeek V3.1

$0.79

Qwen3.5 397B A17B

$2.45

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

DeepSeek V3.1 Quirks & Gotchas

No developer gotchas reported.

Qwen3.5 397B A17B Quirks & Gotchas

No developer gotchas reported.