โ† Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

DeepSeek V3.1 Terminus vs Qwen3.5-Flash

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 Terminus and Qwen3.5-Flash.

DeepSeek

DeepSeek V3.1 Terminus

DeepSeek-V3.1 Terminus is an update to [DeepSeek V3.1](/deepseek/deepseek-chat-v3.1) that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities, further optimizing the model's...

View Full Specs
Alibaba

Qwen3.5-Flash

The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the...

View Full Specs

Technical Specifications

SpecificationDeepSeek V3.1 TerminusQwen3.5-Flash
ProviderDeepSeekAlibaba
Context Window163,840 tokens1,000,000 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelself hostableself hostable
Production Stabilitystablebeta
API AvailableYesYes
Released Date2025-09-222026-02-25

API Pricing Comparison

Input Price per Million Tokens

DeepSeek V3.1 Terminus

$0.27

Qwen3.5-Flash

$0.07

Output Price per Million Tokens

DeepSeek V3.1 Terminus

$0.95

Qwen3.5-Flash

$0.26

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 Terminus Quirks & Gotchas

No developer gotchas reported.

Qwen3.5-Flash Quirks & Gotchas

No developer gotchas reported.