Standard Compute
Model comparison 2026

DeepSeek V3.2 vs Mistral Large 4

DeepSeek V3.2
DeepSeek · Balanced · Open weights
$0.42/1M · 164K ctx
Mistral Large 4
Mistral · Balanced · Open weights
$1.10/1M · 1.0M ctx

Community vote

Pick a winner in each dimension. You can change your vote any time.

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 money
How much capability you get per dollar
Reliability
Consistent results: fewer refusals, loops and format breaks

Specs and pricing side by side

Spec
DeepSeek V3.2
Mistral Large 4
Maker
DeepSeek
Mistral
Blended price / 1M
$0.42
$1.10
Input / output
$0.26 in · $0.80 out / 1M tokens
$0.68 in · $2.09 out / 1M tokens
Context window
164K
1.0M
Open weights
Yes
Yes
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
5.2
7.6
Agentic Ability
4.7
7.1
Speed
7.8
7.0
Value for money
6.3
5.9
Reliability
8.4
8.8

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

Verdict: DeepSeek V3.2 or Mistral Large 4?

Updated 2026-10-13

Choose DeepSeek V3.2 if you want existing V3.2 setups with short prompts. Choose Mistral Large 4 if you want open-weight, EU-provenance agent work that needs long context and image input.

In our editorial scoring, Mistral Large 4 leads in 3 of five dimensions (output quality, agentic ability and reliability), while DeepSeek V3.2 leads in 2. On price, DeepSeek V3.2 runs about $0.42 per 1M tokens (blended) and is open-weight; Mistral Large 4 is about $1.10 and open-weight.

Where DeepSeek V3.2 falls short
  • 164K context, smaller than 27.9% of the coding-agent requests we measured
  • Superseded by DeepSeek V4.1 Flash, which scores higher for less
Full DeepSeek V3.2 breakdown →
Where Mistral Large 4 falls short
  • Still a public preview, so behavior and price can change
  • 26.8% in Artificial Analysis's Terminal-Bench 4.0 run, well below the frontier models
Full Mistral Large 4 breakdown →

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