GPT-3.5 Turbo vs Mistral Large
Mistral Large leads GPT-3.5 Turbo on the Artificial Analysis Intelligence Index, 5.8 to 5.5, and GPT-3.5 Turbo costs 4.0x less per output token ($1.50 vs $6.00 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
GPT-3.5 Turbo or Mistral Large: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-3.5 Turbo for output tokens 4.0x cheaper ($1.50 vs $6.00 per million) and work measured by AA Intelligence Index or GPQA Diamond, where it leads.
- Shared results
- 7
- GPT-3.5 Turbo only
- 6
- Mistral Large only
- 37
- 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
Mistral Large
Mistral Large leads, 5.8 against 5.5.
Same board, both measured
Reasoning
GPQA Diamond
Mistral Large
Mistral Large leads, 47.7% against 30.6%.
Same board, both measured
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 16K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-3.5 Turbo
GPT-3.5 Turbo $0.0013, Mistral Large $0.0050 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo not benchmarked, Mistral Large not benchmarked.
- Widest category
- General, 12.3 points apart on average over 1 shared benchmark.
- Widest single gap
- MedQA (Vals AI): GPT-3.5 Turbo 58.5% against Mistral Large 76.2%, 17.8 points apart on a 0 to 100 scale.
- Output price
- GPT-3.5 Turbo $1.50 against Mistral Large $6.00 per million output tokens, 4.0x apart.
- Context window
- GPT-3.5 Turbo takes 16K tokens, Mistral Large 128K.
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 | GPT-3.5 Turbo | Bars | Mistral Large | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Knowledge | 0 | 3 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 7 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index6 boards, none shared
| Benchmark | GPT-3.5 Turbo | Mistral Large | Leader |
|---|---|---|---|
| AA Coding Index | 10.7 | Not measured | Only GPT-3.5 Turbo measured |
| LiveCodeBench (Vals AI) | Not measured | 37.1% | Only Mistral Large measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 17.8% | Only Mistral Large measured |
| LMArena Text: coding | Not measured | 1275 | Only Mistral Large measured |
| LMArena Text: software and IT | Not measured | 1274 | Only Mistral Large measured |
| SciCode | 0.0% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-3.5 Turbo | Mistral Large | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.5 | 5.8 | Mistral Large |
| Epoch Capabilities Index | Not measured | 122.1 | Only Mistral Large measured |
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | Mistral Large | Leader |
|---|---|---|---|
| Neither model has a result on 41 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-3.5 Turbo | Mistral Large | Leader |
|---|---|---|---|
| GPQA Diamond | 30.6% | 47.7% | Mistral Large |
| GPQA Diamond (Artificial Analysis run) | 29.7% | 35.1% | Mistral Large |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 3.5% | Only Mistral Large measured |
| BIG-Bench Hard | 61.6% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: hard prompts | Not measured | 1257 | Only Mistral Large measured |
| LMArena Text: expert | Not measured | 1208 | Only Mistral Large measured |
| LMArena Text: hard prompts in English | Not measured | 1268 | Only Mistral Large measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-3.5 Turbo | Mistral Large | Leader |
|---|---|---|---|
| AIME | Not measured | 9.2% | Only Mistral Large measured |
| MATH 500 (Vals AI) | Not measured | 74.4% | Only Mistral Large measured |
| MGSM (Vals AI) | Not measured | 87.2% | Only Mistral Large measured |
| GSM8K | 57.8% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: math | Not measured | 1261 | Only Mistral Large measured |
| LMArena Text: mathematical work | Not measured | 1257 | Only Mistral Large measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-3.5 Turbo | Mistral Large | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 69.7% | Only Mistral Large measured |
| LegalBench (Vals AI) | 64.4% | Not measured | Only GPT-3.5 Turbo measured |
| TaxEval (Vals AI) | Not measured | 63.8% | Only Mistral Large measured |
| MedQA (Vals AI) | 58.5% | 76.2% | Mistral Large |
| MMLU Pro (Artificial Analysis run) | 46.2% | 51.5% | Mistral Large |
| MMLU | 68.5% | 68.8% | Mistral Large |
| LMArena Text: science | Not measured | 1260 | Only Mistral Large measured |
| LMArena Text: medicine and healthcare | Not measured | 1255 | Only Mistral Large measured |
| LMArena Text: legal and government | Not measured | 1275 | Only Mistral Large measured |
| LMArena Text: business and finance | Not measured | 1238 | Only Mistral Large measured |
| Neither model has a result on the other 8 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | Mistral Large | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-3.5 Turbo | Mistral Large | Leader |
|---|---|---|---|
| DTBench | 48.5% | 60.8% | Mistral Large |
| LMCA | 9.7% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text | Not measured | 1265 | Only Mistral Large measured |
| LMArena Text: instruction following | Not measured | 1249 | Only Mistral Large measured |
| LMArena Text: creative writing | Not measured | 1242 | Only Mistral Large measured |
| LMArena Text: English | Not measured | 1284 | Only Mistral Large measured |
| LMArena Text: non-English | Not measured | 1235 | Only Mistral Large measured |
| LMArena Text: Chinese | Not measured | 1239 | Only Mistral Large measured |
| LMArena Text: German | Not measured | 1242 | Only Mistral Large measured |
| LMArena Text: Japanese | Not measured | 1170 | Only Mistral Large measured |
| LMArena Text: Korean | Not measured | 1202 | Only Mistral Large measured |
| LMArena Text: French | Not measured | 1325 | Only Mistral Large measured |
| LMArena Text: Spanish | Not measured | 1268 | Only Mistral Large measured |
| LMArena Text: Russian | Not measured | 1252 | Only Mistral Large measured |
| LMArena Text: Polish | Not measured | 1157 | Only Mistral Large measured |
| LMArena Text: multi-turn | Not measured | 1260 | Only Mistral Large measured |
| LMArena Text: longer queries | Not measured | 1261 | Only Mistral Large measured |
| LMArena Text: writing and language | Not measured | 1261 | Only Mistral Large measured |
| LMArena Text: entertainment and media | Not measured | 1230 | Only Mistral Large measured |
| Neither model has a result on the other 27 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-3.5 Turbo | Mistral Large | 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
GPT-3.5 Turbo costs less
Repository review
50K input + 3K output tokens
GPT-3.5 Turbo costs less
Agent loop
200K input + 10K output tokens
GPT-3.5 Turbo 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 | OpenAI GPT-3.5 Turbo | Mistral Large |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | May 28, 2023 | February 26, 2024 |
| Context window | 16K | 128K |
| Input $/Mtok | $0.50 | $2.00 |
| Output $/Mtok | $1.50 | $6.00 |
| 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 GPT-3.5 Turbo better than Mistral Large for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-3.5 Turbo for output tokens 4.0x cheaper ($1.50 vs $6.00 per million) and work measured by AA Intelligence Index or GPQA Diamond, where it leads.
Which is cheaper, GPT-3.5 Turbo or Mistral Large?
GPT-3.5 Turbo costs $0.50 per million input tokens and $1.50 per million output tokens; Mistral Large costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-3.5 Turbo or Mistral Large?
Mistral Large, with 128K tokens against 16K.
How many benchmarks is the GPT-3.5 Turbo vs Mistral Large comparison based on?
7 benchmarks have a result for both models as of October 22, 2026. GPT-3.5 Turbo's coding index rests on 0 independent benchmarks and Mistral Large's on 0. Where only one model has a result, the page says so instead of naming a winner.