Devstral 2 2512 vs GPT-5.6 Luna Pro
GPT-5.6 Luna Pro costs 1.7x less per output token than Devstral 2 2512 ($1.20 vs $2.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $2.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.20
Devstral 2 2512 or GPT-5.6 Luna Pro: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. Devstral 2 2512 has results on SWE-bench Verified, AA Coding Index and LiveCodeBench (Vals AI); GPT-5.6 Luna Pro has none yet. 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
Intelligence
AA Intelligence Index
No call
Only Devstral 2 2512 has a AA Intelligence Index result, 8.6.
Directional only
Agentic work
AA Agentic Index
No call
Only Devstral 2 2512 has a AA Agentic Index result, 2.3.
Directional only
Long documents
Listed context window
GPT-5.6 Luna Pro
GPT-5.6 Luna Pro takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.6 Luna Pro
Devstral 2 2512 $0.0014, GPT-5.6 Luna Pro $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Devstral 2 2512 has the number, $1.19.
Directional only
At a glance
- Coding index
- Devstral 2 2512 not benchmarked, GPT-5.6 Luna 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
- Devstral 2 2512 $2.00 against GPT-5.6 Luna Pro $1.20 per million output tokens, 1.7x apart.
- Context window
- Devstral 2 2512 takes 262K tokens, GPT-5.6 Luna 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 Index4 boards measured
| Benchmark | Devstral 2 2512 | GPT-5.6 Luna Pro | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.8% | Not measured | Only Devstral 2 2512 measured |
| AA Coding Index | 31.3 | Not measured | Only Devstral 2 2512 measured |
| LiveCodeBench (Vals AI) | 51.8% | Not measured | Only Devstral 2 2512 measured |
| SWE-bench Verified (Vals AI) | 62.8% | Not measured | Only Devstral 2 2512 measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Devstral 2 2512 | GPT-5.6 Luna Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 8.6 | Not measured | Only Devstral 2 2512 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Devstral 2 2512 | GPT-5.6 Luna Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 2.3 | Not measured | Only Devstral 2 2512 measured |
| Neither model has a result on the other 40 boards here | |||
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
GPT-5.6 Luna Pro costs less
Repository review
50K input + 3K output tokens
GPT-5.6 Luna Pro costs less
Agent loop
200K input + 10K output tokens
GPT-5.6 Luna Pro 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 Devstral 2 2512 | OpenAI GPT-5.6 Luna Pro |
|---|---|---|
| Maker | Mistral AI | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | December 9, 2025 | July 9, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.40 | $0.20 |
| Output $/Mtok | $2.00 | $1.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $1.19 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Devstral 2 2512 better than GPT-5.6 Luna Pro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Devstral 2 2512 or GPT-5.6 Luna Pro?
Devstral 2 2512 costs $0.40 per million input tokens and $2.00 per million output tokens; GPT-5.6 Luna Pro costs $0.20 and $1.20. Cost per solved task is known for Devstral 2 2512 only.
Which has the bigger context window, Devstral 2 2512 or GPT-5.6 Luna Pro?
GPT-5.6 Luna Pro, with 1.05M tokens against 262K.
Has any benchmark tested both Devstral 2 2512 and GPT-5.6 Luna Pro?
No benchmark has tested both yet. Devstral 2 2512 has results on SWE-bench Verified, AA Coding Index and LiveCodeBench (Vals AI); GPT-5.6 Luna Pro has none yet. Compare them on price and context instead. Data as of October 21, 2026.