Mistral Large vs Sonar
Sonar leads Mistral Large on the Artificial Analysis Intelligence Index, 7.7 to 5.8, and Sonar costs 6.0x less per output token ($1.00 vs $6.00 per million). Updated October 21, 2026; 5 benchmarks have a result for both.
Mistral Large or Sonar: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Large for a larger context window (128K against 127K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.
- Shared results
- 5
- Mistral Large only
- 39
- Sonar only
- 0
- Like-for-like categories
- 4 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
Sonar
Sonar leads, 7.7 against 5.8.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Mistral Large has a GPQA Diamond result, 47.7%.
Directional only
Math
AIME
No call
Only Mistral Large has a AIME result, 9.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Large has a MMLU Pro result, 69.7%.
Directional only
Long documents
Listed context window
Mistral Large
Mistral Large takes 128K tokens against 127K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Sonar
Mistral Large $0.0050, Sonar $0.0015 per turn.
List prices
At a glance
- Coding index
- Mistral Large not benchmarked, Sonar not benchmarked.
- Widest category
- Knowledge, 17.4 points apart on average over 1 shared benchmark.
- Widest single gap
- MMLU Pro (Artificial Analysis run): Mistral Large 51.5% against Sonar 68.9%, 17.4 points apart on a 0 to 100 scale.
- Output price
- Mistral Large $6.00 against Sonar $1.00 per million output tokens, 6.0x apart.
- Context window
- Mistral Large takes 128K tokens, Sonar 127K.
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 | Mistral Large | Bars | Sonar | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Knowledge | 0 | 1 | ||
| All shared boards | 0 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Mistral Large | Sonar | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | 37.1% | Not measured | Only Mistral Large measured |
| LiveCodeBench (Artificial Analysis run) | 17.8% | 29.5% | Sonar |
| LMArena Text: coding | 1275 | Not measured | Only Mistral Large measured |
| LMArena Text: software and IT | 1274 | Not measured | Only Mistral Large measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large | Sonar | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.8 | 7.7 | Sonar |
| Epoch Capabilities Index | 122.1 | Not measured | Only Mistral Large measured |
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large | Sonar | Leader |
|---|---|---|---|
| Neither model has a result on 41 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Large | Sonar | Leader |
|---|---|---|---|
| GPQA Diamond | 47.7% | Not measured | Only Mistral Large measured |
| GPQA Diamond (Artificial Analysis run) | 35.1% | 47.1% | Sonar |
| Humanity's Last Exam (Artificial Analysis run) | 3.5% | 4.9% | Sonar |
| LMArena Text: hard prompts | 1257 | Not measured | Only Mistral Large measured |
| LMArena Text: expert | 1208 | Not measured | Only Mistral Large measured |
| LMArena Text: hard prompts in English | 1268 | Not measured | Only Mistral Large measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Mistral Large | Sonar | Leader |
|---|---|---|---|
| AIME | 9.2% | Not measured | Only Mistral Large measured |
| MATH 500 (Vals AI) | 74.4% | Not measured | Only Mistral Large measured |
| MGSM (Vals AI) | 87.2% | Not measured | Only Mistral Large measured |
| LMArena Text: math | 1261 | Not measured | Only Mistral Large measured |
| LMArena Text: mathematical work | 1257 | Not measured | Only Mistral Large measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large | Sonar | Leader |
|---|---|---|---|
| MMLU Pro | 69.7% | Not measured | Only Mistral Large measured |
| TaxEval (Vals AI) | 63.8% | Not measured | Only Mistral Large measured |
| MedQA (Vals AI) | 76.2% | Not measured | Only Mistral Large measured |
| MMLU Pro (Artificial Analysis run) | 51.5% | 68.9% | Sonar |
| MMLU | 68.8% | Not measured | Only Mistral Large measured |
| LMArena Text: science | 1260 | Not measured | Only Mistral Large measured |
| LMArena Text: medicine and healthcare | 1255 | Not measured | Only Mistral Large measured |
| LMArena Text: legal and government | 1275 | Not measured | Only Mistral Large measured |
| LMArena Text: business and finance | 1238 | Not measured | Only Mistral Large measured |
| Neither model has a result on the other 9 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large | Sonar | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | Mistral Large | Sonar | Leader |
|---|---|---|---|
| DTBench | 60.8% | Not measured | Only Mistral Large measured |
| LMArena Text | 1265 | Not measured | Only Mistral Large measured |
| LMArena Text: instruction following | 1249 | Not measured | Only Mistral Large measured |
| LMArena Text: creative writing | 1242 | Not measured | Only Mistral Large measured |
| LMArena Text: English | 1284 | Not measured | Only Mistral Large measured |
| LMArena Text: non-English | 1235 | Not measured | Only Mistral Large measured |
| LMArena Text: Chinese | 1239 | Not measured | Only Mistral Large measured |
| LMArena Text: German | 1242 | Not measured | Only Mistral Large measured |
| LMArena Text: Japanese | 1170 | Not measured | Only Mistral Large measured |
| LMArena Text: Korean | 1202 | Not measured | Only Mistral Large measured |
| LMArena Text: French | 1325 | Not measured | Only Mistral Large measured |
| LMArena Text: Spanish | 1268 | Not measured | Only Mistral Large measured |
| LMArena Text: Russian | 1252 | Not measured | Only Mistral Large measured |
| LMArena Text: Polish | 1157 | Not measured | Only Mistral Large measured |
| LMArena Text: multi-turn | 1260 | Not measured | Only Mistral Large measured |
| LMArena Text: longer queries | 1261 | Not measured | Only Mistral Large measured |
| LMArena Text: writing and language | 1261 | Not measured | Only Mistral Large measured |
| LMArena Text: entertainment and media | 1230 | Not measured | Only Mistral Large measured |
| Neither model has a result on the other 28 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large | Sonar | 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
Sonar costs less
Repository review
50K input + 3K output tokens
Sonar costs less
Agent loop
200K input + 10K output tokens
Sonar 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 Large | Perplexity Sonar |
|---|---|---|
| Maker | Mistral AI | Perplexity |
| Weights | No public weights listed | No public weights listed |
| Released | February 26, 2024 | January 27, 2025 |
| Context window | 128K | 127K |
| Input $/Mtok | $2.00 | $1.00 |
| Output $/Mtok | $6.00 | $1.00 |
| 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 Mistral Large better than Sonar for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Large for a larger context window (128K against 127K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.
Which is cheaper, Mistral Large or Sonar?
Mistral Large costs $2.00 per million input tokens and $6.00 per million output tokens; Sonar costs $1.00 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Large or Sonar?
Mistral Large, with 128K tokens against 127K.
How many benchmarks is the Mistral Large vs Sonar comparison based on?
5 benchmarks have a result for both models as of October 21, 2026. Mistral Large's coding index rests on 0 independent benchmarks and Sonar's on 0. Where only one model has a result, the page says so instead of naming a winner.