Standard Compute
Model comparison 2026

Codestral vs GPT-6 Luna

Codestral
Mistral · Budget · Proprietary
$0.48/1M · 256K ctx
GPT-6 Luna
OpenAI · Budget · Proprietary
$0.22/1M · 1.1M 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
Codestral
GPT-6 Luna
Maker
Mistral
OpenAI
Blended price / 1M
$0.48
$0.22
Input / output
$0.30 in · $0.90 out / 1M tokens
$0.10 in · $0.50 out / 1M tokens
Context window
256K
1.1M
Open weights
No
No
Tool use
Yes
Yes
Reasoning
No
Yes
Output Quality
6.8
8.7
Agentic Ability
6.5
8.5
Speed
9.5
9.3
Value for money
8.9
9.4
Reliability
8.8
9.1

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

Verdict: Codestral or GPT-6 Luna?

Updated 2026-10-13

Choose Codestral if you want fast completions and lightweight code edits. Choose GPT-6 Luna if you want cheap, fast subtasks, routing and subagents in OpenAI-based stacks.

In our editorial scoring, GPT-6 Luna leads in 4 of five dimensions (output quality, agentic ability, value for money and reliability), while Codestral leads in 1. On price, Codestral runs about $0.48 per 1M tokens (blended) and is proprietary; GPT-6 Luna is about $0.22 and proprietary.

Where Codestral falls short
  • Not for deep agentic planning
  • Quality below the larger coders
Full Codestral breakdown →
Where GPT-6 Luna falls short
  • Weak on long agentic runs (16.4% on Terminal-Bench 4.0)
  • Clear quality step below GPT-6.1 Sol
Full GPT-6 Luna breakdown →

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