Standard Compute
Model Comparison 2026

DeepSeek V3.2 vs Qwen3 235B A22B

DeepSeek V3.2
DeepSeek · Balanced · Open weights
$0.31/1M · 164K ctx
Qwen3 235B A22B
Alibaba (Qwen) · Budget · Open weights
$0.23/1M · 262K ctx

Community Vote

Pick a winner in each dimension — change your vote anytime.

Output Quality
Correctness and depth of what it produces
Agentic Ability
Tool calls, instruction-following, and multi-step tasks
Speed
Tokens per second and time-to-first-token
Value for $
How much capability you get per dollar
Reliability
Consistent results — fewer refusals, loops, and format breaks

Specs & Pricing, Side by Side

Spec
DeepSeek V3.2
Qwen3 235B
Maker
DeepSeek
Alibaba (Qwen)
Blended price / 1M
$0.31
$0.23
Input / output
$0.27 in · $0.40 out / 1M tokens
$0.09 in · $0.55 out / 1M tokens
Context window
164K
262K
Open weights
Yes
Yes
Tool use
Yes
Yes
Reasoning
Yes
No
Output Quality
7.6
8.0
Agentic Ability
7.4
8.0
Speed
7.8
8.2
Value for $
9.4
10.0
Reliability
8.6
8.8

Pricing and capabilities synced from the OpenRouter catalogue. Scores are editorial (0–10).

Verdict: DeepSeek V3.2 or Qwen3 235B?

Updated 2026-08-02

Choose DeepSeek V3.2 if you want dependable open-weight output on a tight budget. Choose Qwen3 235B A22B if you want self-hosted or ultra-cheap open-weight agents.

In our editorial scoring, Qwen3 235B A22B leads in 5 of five dimensions (output quality, agentic ability, speed, value for $ and reliability), while DeepSeek V3.2 leads in 0. On price, DeepSeek V3.2 runs about $0.31 per 1M tokens (blended) and is open-weight; Qwen3 235B A22B is about $0.23 and open-weight.

Where DeepSeek V3.2 falls short
  • Shorter 128K context
  • Superseded by V4 on quality
Full DeepSeek V3.2 breakdown →
Where Qwen3 235B falls short
  • Behind frontier models on quality
  • Needs real GPUs to self-host well
Full Qwen3 235B breakdown →

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