Codestral 2508 vs GPT-5.6 Sol Pro
Codestral 2508 costs 22.2x less per output token than GPT-5.6 Sol Pro ($0.90 vs $20.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.90
- Coding
- No data
- Overall
- No data
- Output $/M
- $20.00
Codestral 2508 or GPT-5.6 Sol Pro: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Codestral 2508 for output tokens 22.2x cheaper ($0.90 vs $20.00 per million).
No benchmark has tested both yet. Codestral 2508 has results on ALE-Bench, Design Arena: websites and Design Arena: UI components; GPT-5.6 Sol Pro on WeirdML, APEX-Agents and SimpleBench. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Web design
Design Arena: websites
No call
Only Codestral 2508 has a Design Arena: websites result, 1013.
Directional only
Long documents
Listed context window
GPT-5.6 Sol Pro
GPT-5.6 Sol Pro takes 1.05M tokens against 256K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Codestral 2508
Codestral 2508 $0.0008, GPT-5.6 Sol Pro $0.014 per turn.
List prices
At a glance
- Coding index
- Codestral 2508 not benchmarked, GPT-5.6 Sol Pro not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Codestral 2508 $0.90 against GPT-5.6 Sol Pro $20.00 per million output tokens, 22.2x apart.
- Context window
- Codestral 2508 takes 256K tokens, GPT-5.6 Sol Pro 1.05M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Codestral 2508 | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| APEX-Agents | Not measured | 51.4% | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Codestral 2508 | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| SimpleBench | Not measured | 71.7% | Only GPT-5.6 Sol Pro measured |
| Chess puzzles | Not measured | 68.0% | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Codestral 2508 | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| FrontierMath, tier 4 | Not measured | 80.5% | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Codestral 2508 | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1013 | Not measured | Only Codestral 2508 measured |
| Design Arena: UI components | 1017 | Not measured | Only Codestral 2508 measured |
| Design Arena: game dev | 968 | Not measured | Only Codestral 2508 measured |
| Design Arena: data viz | 1017 | Not measured | Only Codestral 2508 measured |
| Design Arena: 3D | 1020 | Not measured | Only Codestral 2508 measured |
| Design Arena: all code categories | 1007 | Not measured | Only Codestral 2508 measured |
| Neither model has a result on the other 3 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Codestral 2508 costs less
Repository review
50K input + 3K output tokens
Codestral 2508 costs less
Agent loop
200K input + 10K output tokens
Codestral 2508 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Mistral Codestral 2508 | OpenAI GPT-5.6 Sol Pro |
|---|---|---|
| Maker | Mistral AI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | August 1, 2025 | July 9, 2026 |
| Context window | 256K | 1.05M |
| Input $/Mtok | $0.30 | $4.00 |
| Output $/Mtok | $0.90 | $20.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Codestral 2508 better than GPT-5.6 Sol Pro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Codestral 2508 for output tokens 22.2x cheaper ($0.90 vs $20.00 per million).
Which is cheaper, Codestral 2508 or GPT-5.6 Sol Pro?
Codestral 2508 costs $0.30 per million input tokens and $0.90 per million output tokens; GPT-5.6 Sol Pro costs $4.00 and $20.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Codestral 2508 or GPT-5.6 Sol Pro?
GPT-5.6 Sol Pro, with 1.05M tokens against 256K.
Has any benchmark tested both Codestral 2508 and GPT-5.6 Sol Pro?
No benchmark has tested both yet. Codestral 2508 has results on ALE-Bench, Design Arena: websites and Design Arena: UI components; GPT-5.6 Sol Pro on WeirdML, APEX-Agents and SimpleBench. Compare them on price and context instead. Data as of October 21, 2026.