Llama 3.1 8B Instruct vs Mistral Large
Llama 3.1 8B Instruct leads Mistral Large on the Artificial Analysis Intelligence Index, 6.9 to 5.8, and Llama 3.1 8B Instruct costs 75.0x less per output token ($0.08 vs $6.00 per million). Updated October 21, 2026; 35 benchmarks have a result for both.
Llama 3.1 8B Instruct or Mistral Large: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Llama 3.1 8B Instruct for output tokens 75.0x cheaper ($0.08 vs $6.00 per million) and a larger context window (131K against 128K tokens).
- Shared results
- 35
- Llama 3.1 8B Instruct only
- 16
- Mistral Large only
- 9
- Like-for-like categories
- 6 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
Llama 3.1 8B Instruct
Llama 3.1 8B Instruct leads, 6.9 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
Llama 3.1 8B Instruct
Llama 3.1 8B Instruct takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.1 8B Instruct
Llama 3.1 8B Instruct $0.0001, Mistral Large $0.0050 per turn.
List prices
At a glance
- Coding index
- Llama 3.1 8B Instruct not benchmarked, Mistral Large not benchmarked.
- Widest category
- General, 15.7 points apart on average over 17 shared benchmarks.
- Widest single gap
- LMArena Text: Korean: Llama 3.1 8B Instruct 1053 against Mistral Large 1202, 24.8 points apart on a 0 to 100 scale.
- Output price
- Llama 3.1 8B Instruct $0.08 against Mistral Large $6.00 per million output tokens, 75.0x apart.
- Context window
- Llama 3.1 8B Instruct takes 131K 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 | Llama 3.1 8B Instruct | Bars | Mistral Large | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 1 | 1 | ||
| Reasoning | 1 | 4 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 6 | ||
| General | 0 | 17 | ||
| All shared boards | 2 | 33 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Llama 3.1 8B Instruct | Mistral Large | Leader |
|---|---|---|---|
| AA Coding Index | 5.4 | Not measured | Only Llama 3.1 8B Instruct measured |
| LiveCodeBench (Vals AI) | Not measured | 37.1% | Only Mistral Large measured |
| LiveCodeBench (Artificial Analysis run) | 11.6% | 17.8% | Mistral Large |
| Terminal-Bench Hard (Artificial Analysis run) | 0.8% | Not measured | Only Llama 3.1 8B Instruct measured |
| WeirdML | 1.7% | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: coding | 1195 | 1275 | Mistral Large |
| LMArena Text: software and IT | 1195 | 1274 | Mistral Large |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Llama 3.1 8B Instruct | Mistral Large | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.9 | 5.8 | Llama 3.1 8B Instruct |
| Epoch Capabilities Index | 116.5 | 122.1 | Mistral Large |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Llama 3.1 8B Instruct | Mistral Large | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 16.4% | Not measured | Only Llama 3.1 8B Instruct measured |
| BALROG | 15.1% | Not measured | Only Llama 3.1 8B Instruct measured |
| Berkeley Function Calling Leaderboard (BFCL) | 25.8% | Not measured | Only Llama 3.1 8B Instruct measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | Llama 3.1 8B Instruct | Mistral Large | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 47.7% | Only Mistral Large measured |
| GPQA Diamond (Artificial Analysis run) | 25.9% | 35.1% | Mistral Large |
| Humanity's Last Exam (Artificial Analysis run) | 5.3% | 3.5% | Llama 3.1 8B Instruct |
| GPQA Diamond (Epoch AI run) | 27.0% | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: hard prompts | 1175 | 1257 | Mistral Large |
| LMArena Text: expert | 1144 | 1208 | Mistral Large |
| LMArena Text: hard prompts in English | 1196 | 1268 | Mistral Large |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Llama 3.1 8B Instruct | 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 |
| AA Math Index | 4.3 | Not measured | Only Llama 3.1 8B Instruct measured |
| AIME 2025 (Artificial Analysis run) | 4.3% | Not measured | Only Llama 3.1 8B Instruct measured |
| OTIS Mock AIME | 1.7% | Not measured | Only Llama 3.1 8B Instruct measured |
| MATH level 5 | 22.9% | Not measured | Only Llama 3.1 8B Instruct measured |
| GSM8K | 82.4% | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text: math | 1179 | 1261 | Mistral Large |
| LMArena Text: mathematical work | 1180 | 1257 | Mistral Large |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Llama 3.1 8B Instruct | Mistral Large | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 69.7% | Only Mistral Large measured |
| TaxEval (Vals AI) | Not measured | 63.8% | Only Mistral Large measured |
| MedQA (Vals AI) | Not measured | 76.2% | Only Mistral Large measured |
| MMLU Pro (Artificial Analysis run) | 47.6% | 51.5% | Mistral Large |
| MMLU | 56.1% | 68.8% | Mistral Large |
| LMArena Text: science | 1193 | 1260 | Mistral Large |
| LMArena Text: medicine and healthcare | 1182 | 1255 | Mistral Large |
| LMArena Text: legal and government | 1206 | 1275 | Mistral Large |
| LMArena Text: business and finance | 1166 | 1238 | Mistral Large |
| 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 | Llama 3.1 8B Instruct | Mistral Large | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
| Benchmark | Llama 3.1 8B Instruct | Mistral Large | Leader |
|---|---|---|---|
| IFBench | 28.6% | Not measured | Only Llama 3.1 8B Instruct measured |
| Long context reasoning (AA-LCR) | 18.0% | Not measured | Only Llama 3.1 8B Instruct measured |
| DTBench | 50.9% | 60.8% | Mistral Large |
| LMCA | 5.4% | Not measured | Only Llama 3.1 8B Instruct measured |
| PIQA | 81.2% | Not measured | Only Llama 3.1 8B Instruct measured |
| LMArena Text | 1187 | 1265 | Mistral Large |
| LMArena Text: instruction following | 1159 | 1249 | Mistral Large |
| LMArena Text: creative writing | 1154 | 1242 | Mistral Large |
| LMArena Text: English | 1218 | 1284 | Mistral Large |
| LMArena Text: non-English | 1148 | 1235 | Mistral Large |
| LMArena Text: Chinese | 1151 | 1239 | Mistral Large |
| LMArena Text: German | 1144 | 1242 | Mistral Large |
| LMArena Text: Japanese | 1061 | 1170 | Mistral Large |
| LMArena Text: Korean | 1053 | 1202 | Mistral Large |
| LMArena Text: French | 1178 | 1325 | Mistral Large |
| LMArena Text: Spanish | 1169 | 1268 | Mistral Large |
| LMArena Text: Russian | 1158 | 1252 | Mistral Large |
| LMArena Text: Polish | Not measured | 1157 | Only Mistral Large measured |
| LMArena Text: multi-turn | 1172 | 1260 | Mistral Large |
| LMArena Text: longer queries | 1181 | 1261 | Mistral Large |
| LMArena Text: writing and language | 1162 | 1261 | Mistral Large |
| LMArena Text: entertainment and media | 1145 | 1230 | Mistral Large |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Llama 3.1 8B Instruct | 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
Llama 3.1 8B Instruct costs less
Repository review
50K input + 3K output tokens
Llama 3.1 8B Instruct costs less
Agent loop
200K input + 10K output tokens
Llama 3.1 8B Instruct 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 | Meta Llama 3.1 8B Instruct | Mistral Large |
|---|---|---|
| Maker | Meta Llama | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | July 23, 2024 | February 26, 2024 |
| Context window | 131K | 128K |
| Input $/Mtok | $0.05 | $2.00 |
| Output $/Mtok | $0.08 | $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 Llama 3.1 8B Instruct better than Mistral Large for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Llama 3.1 8B Instruct for output tokens 75.0x cheaper ($0.08 vs $6.00 per million) and a larger context window (131K against 128K tokens).
Which is cheaper, Llama 3.1 8B Instruct or Mistral Large?
Llama 3.1 8B Instruct costs $0.05 per million input tokens and $0.08 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, Llama 3.1 8B Instruct or Mistral Large?
Llama 3.1 8B Instruct, with 131K tokens against 128K.
How many benchmarks is the Llama 3.1 8B Instruct vs Mistral Large comparison based on?
35 benchmarks have a result for both models as of October 21, 2026. Llama 3.1 8B Instruct'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.