Standard Compute
Model comparison 2026

GLM 4.6 vs Mistral Large 4

GLM 4.6
Z.AI · Balanced · Open weights
$0.95/1M · 205K 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
GLM 4.6
Mistral Large 4
Maker
Z.AI
Mistral
Blended price / 1M
$0.95
$1.10
Input / output
$0.50 in · $2.00 out / 1M tokens
$0.68 in · $2.09 out / 1M tokens
Context window
205K
1.0M
Open weights
Yes
Yes
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
4.8
7.6
Agentic Ability
4.6
7.1
Speed
5.5
7.0
Value for money
5.9
5.9
Reliability
8.4
8.8

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

Verdict: GLM 4.6 or Mistral Large 4?

Updated 2026-10-13

Choose GLM 4.6 if you want short-context coding tasks on a tight budget. 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 4 of five dimensions (output quality, agentic ability, speed and reliability), while GLM 4.6 leads in 0. On price, GLM 4.6 runs about $0.95 per 1M tokens (blended) and is open-weight; Mistral Large 4 is about $1.10 and open-weight.

Where GLM 4.6 falls short
  • 202K context, smaller than 19.7% of the coding-agent requests we measured
  • Superseded by the GLM 5 line; GLM 5.3 scores far higher
Full GLM 4.6 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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