Devstral 2 2512 vs Gemma 3 27B
Devstral 2 2512 leads Gemma 3 27B on the Artificial Analysis Intelligence Index, 8.6 to 4.9, and Gemma 3 27B costs 6.7x less per output token ($0.30 vs $2.00 per million). Updated October 22, 2026; 3 benchmarks have a result for both.
Devstral 2 2512 or Gemma 3 27B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Devstral 2 2512 for a larger context window (262K against 131K tokens).
- Shared results
- 3
- Devstral 2 2512 only
- 3
- Gemma 3 27B only
- 63
- Like-for-like categories
- 3 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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
Devstral 2 2512
Devstral 2 2512 leads, 8.6 against 4.9.
Same board, both measured
Agentic work
AA Agentic Index
Devstral 2 2512
Devstral 2 2512 leads, 2.3 against 0.1.
Same board, both measured
Long documents
Listed context window
Devstral 2 2512
Devstral 2 2512 takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 3 27B
Devstral 2 2512 $0.0014, Gemma 3 27B $0.0002 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, Gemma 3 27B not benchmarked.
- Widest category
- Coding, 21.2 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Coding Index: Devstral 2 2512 31.3 against Gemma 3 27B 10.1, 21.2 points apart on a 0 to 100 scale.
- Output price
- Devstral 2 2512 $2.00 against Gemma 3 27B $0.30 per million output tokens, 6.7x apart.
- Context window
- Devstral 2 2512 takes 262K tokens, Gemma 3 27B 131K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Devstral 2 2512 | Bars | Gemma 3 27B | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| All shared boards | 3 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | Devstral 2 2512 | Gemma 3 27B | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 4.9% | Only Gemma 3 27B measured |
| SWE-bench Verified | 53.8% | Not measured | Only Devstral 2 2512 measured |
| AA Coding Index | 31.3 | 10.1 | Devstral 2 2512 |
| 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 |
| LiveCodeBench (Artificial Analysis run) | Not measured | 13.7% | Only Gemma 3 27B measured |
| SciCode | Not measured | 23.3% | Only Gemma 3 27B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 3.8% | Only Gemma 3 27B measured |
| LMArena Text: coding | Not measured | 1322 | Only Gemma 3 27B measured |
| LMArena Text: software and IT | Not measured | 1354 | Only Gemma 3 27B measured |
| SciCode | Not measured | 0.0% | Only Gemma 3 27B measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Devstral 2 2512 | Gemma 3 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 8.6 | 4.9 | Devstral 2 2512 |
| Epoch Capabilities Index | Not measured | 130.0 | Only Gemma 3 27B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Devstral 2 2512 | Gemma 3 27B | Leader |
|---|---|---|---|
| AA Agentic Index | 2.3 | 0.1 | Devstral 2 2512 |
| τ²-Bench Telecom | Not measured | 10.5% | Only Gemma 3 27B measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 29.5% | Only Gemma 3 27B measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Devstral 2 2512 | Gemma 3 27B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 42.8% | Only Gemma 3 27B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 4.4% | Only Gemma 3 27B measured |
| GPQA Diamond (Epoch AI run) | Not measured | 47.7% | Only Gemma 3 27B measured |
| LMArena Text: hard prompts | Not measured | 1340 | Only Gemma 3 27B measured |
| LMArena Text: expert | Not measured | 1304 | Only Gemma 3 27B measured |
| LMArena Text: hard prompts in English | Not measured | 1353 | Only Gemma 3 27B measured |
| LMArena Vision: diagrams | Not measured | 1156 | Only Gemma 3 27B measured |
| LMArena Vision: homework | Not measured | 1160 | Only Gemma 3 27B measured |
| Kagi LLM Benchmark | Not measured | 35.1% | Only Gemma 3 27B measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Devstral 2 2512 | Gemma 3 27B | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 20.7 | Only Gemma 3 27B measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 20.7% | Only Gemma 3 27B measured |
| OTIS Mock AIME | Not measured | 22.5% | Only Gemma 3 27B measured |
| MATH level 5 | Not measured | 74.0% | Only Gemma 3 27B measured |
| LMArena Text: math | Not measured | 1312 | Only Gemma 3 27B measured |
| LMArena Text: mathematical work | Not measured | 1327 | Only Gemma 3 27B measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Devstral 2 2512 | Gemma 3 27B | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 66.9% | Only Gemma 3 27B measured |
| GeoBench | Not measured | 52.0% | Only Gemma 3 27B measured |
| LMArena Text: science | Not measured | 1383 | Only Gemma 3 27B measured |
| LMArena Text: medicine and healthcare | Not measured | 1391 | Only Gemma 3 27B measured |
| LMArena Text: legal and government | Not measured | 1375 | Only Gemma 3 27B measured |
| LMArena Text: business and finance | Not measured | 1360 | Only Gemma 3 27B measured |
| FACTS Benchmark Suite | Not measured | 29.1% | Only Gemma 3 27B measured |
| Neither model has a result on the other 11 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Devstral 2 2512 | Gemma 3 27B | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index31 boards, none shared
| Benchmark | Devstral 2 2512 | Gemma 3 27B | Leader |
|---|---|---|---|
| IFBench | Not measured | 31.8% | Only Gemma 3 27B measured |
| Long context reasoning (AA-LCR) | Not measured | 7.3% | Only Gemma 3 27B measured |
| DTBench | Not measured | 52.5% | Only Gemma 3 27B measured |
| LMCA | Not measured | 12.3% | Only Gemma 3 27B measured |
| Fiction.LiveBench | Not measured | 33.3% | Only Gemma 3 27B measured |
| Creative writing (Lech Mazur) | Not measured | 79.9% | Only Gemma 3 27B measured |
| LMArena Text | Not measured | 1358 | Only Gemma 3 27B measured |
| LMArena Text: instruction following | Not measured | 1321 | Only Gemma 3 27B measured |
| LMArena Text: creative writing | Not measured | 1345 | Only Gemma 3 27B measured |
| LMArena Vision | Not measured | 1165 | Only Gemma 3 27B measured |
| LMArena Text: English | Not measured | 1377 | Only Gemma 3 27B measured |
| LMArena Text: non-English | Not measured | 1334 | Only Gemma 3 27B measured |
| LMArena Text: Chinese | Not measured | 1346 | Only Gemma 3 27B measured |
| LMArena Text: German | Not measured | 1362 | Only Gemma 3 27B measured |
| LMArena Text: Japanese | Not measured | 1287 | Only Gemma 3 27B measured |
| LMArena Text: Korean | Not measured | 1308 | Only Gemma 3 27B measured |
| LMArena Text: French | Not measured | 1368 | Only Gemma 3 27B measured |
| LMArena Text: Spanish | Not measured | 1349 | Only Gemma 3 27B measured |
| LMArena Text: Russian | Not measured | 1349 | Only Gemma 3 27B measured |
| LMArena Text: Polish | Not measured | 1345 | Only Gemma 3 27B measured |
| LMArena Text: multi-turn | Not measured | 1345 | Only Gemma 3 27B measured |
| LMArena Text: longer queries | Not measured | 1333 | Only Gemma 3 27B measured |
| LMArena Text: writing and language | Not measured | 1347 | Only Gemma 3 27B measured |
| LMArena Text: entertainment and media | Not measured | 1320 | Only Gemma 3 27B measured |
| LMArena Vision: English | Not measured | 1188 | Only Gemma 3 27B measured |
| LMArena Vision: Chinese | Not measured | 1164 | Only Gemma 3 27B measured |
| LMArena Vision: reading text | Not measured | 1156 | Only Gemma 3 27B measured |
| LMArena Vision: humor | Not measured | 1166 | Only Gemma 3 27B measured |
| LMArena Vision: captioning | Not measured | 1151 | Only Gemma 3 27B measured |
| LMArena Vision: recognizing things | Not measured | 1196 | Only Gemma 3 27B measured |
| LMArena Vision: creative writing | Not measured | 1177 | Only Gemma 3 27B measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Devstral 2 2512 | Gemma 3 27B | Leader |
|---|---|---|---|
| Neither model has a result on 5 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
Gemma 3 27B costs less
Repository review
50K input + 3K output tokens
Gemma 3 27B costs less
Agent loop
200K input + 10K output tokens
Gemma 3 27B 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 | Google Gemma 3 27B |
|---|---|---|
| Maker | Mistral AI | |
| Weights | Open weights | Open weights |
| Released | December 9, 2025 | March 12, 2025 |
| Context window | 262K | 131K |
| Input $/Mtok | $0.40 | $0.08 |
| Output $/Mtok | $2.00 | $0.30 |
| 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 Gemma 3 27B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Devstral 2 2512 for a larger context window (262K against 131K tokens).
Which is cheaper, Devstral 2 2512 or Gemma 3 27B?
Devstral 2 2512 costs $0.40 per million input tokens and $2.00 per million output tokens; Gemma 3 27B costs $0.08 and $0.30. Cost per solved task is known for Devstral 2 2512 only.
Which has the bigger context window, Devstral 2 2512 or Gemma 3 27B?
Devstral 2 2512, with 262K tokens against 131K.
How many benchmarks is the Devstral 2 2512 vs Gemma 3 27B comparison based on?
3 benchmarks have a result for both models as of October 22, 2026. Devstral 2 2512's coding index rests on 1 independent benchmark and Gemma 3 27B's on 0. Where only one model has a result, the page says so instead of naming a winner.