Command A vs Llama 3.1 8B Instruct
Command A leads Llama 3.1 8B Instruct on the Artificial Analysis Intelligence Index, 13.1 to 6.9, and Llama 3.1 8B Instruct costs 125.0x less per output token ($0.08 vs $10.00 per million). Updated October 21, 2026; 42 benchmarks have a result for both.
Command A or Llama 3.1 8B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Command A for a larger context window (256K against 131K tokens).
- Shared results
- 42
- Command A only
- 20
- Llama 3.1 8B Instruct only
- 9
- Like-for-like categories
- 7 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
Command A
Command A leads, 13.1 against 6.9.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Command A has a AA Agentic Index result, 1.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Command A has a GPQA Diamond result, 48.5%.
Directional only
Math
AIME
No call
Only Command A has a AIME result, 13.3%.
Directional only
Knowledge
MMLU Pro
No call
Only Command A has a MMLU Pro result, 69.2%.
Directional only
Long documents
Listed context window
Command A
Command A takes 256K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.1 8B Instruct
Command A $0.0075, Llama 3.1 8B Instruct $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Command A has the number, $2.69.
Directional only
At a glance
- Coding index
- Command A not benchmarked, Llama 3.1 8B Instruct not benchmarked.
- Widest category
- Agentic work, 42.5 points apart on average over 2 shared benchmarks.
- Widest single gap
- τ²-Bench Telecom: Command A 80.7% against Llama 3.1 8B Instruct 16.4%, 64.3 points apart on a 0 to 100 scale.
- Output price
- Command A $10.00 against Llama 3.1 8B Instruct $0.08 per million output tokens, 125.0x apart.
- Context window
- Command A takes 256K tokens, Llama 3.1 8B Instruct 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 | Command A | Bars | Llama 3.1 8B Instruct | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 4 | 0 | ||
| Knowledge | 5 | 0 | ||
| General | 20 | 0 | ||
| All shared boards | 42 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
| Benchmark | Command A | Llama 3.1 8B Instruct | Leader |
|---|---|---|---|
| AA Coding Index | 27.8 | 5.4 | Command A |
| LiveCodeBench (Vals AI) | 35.1% | Not measured | Only Command A measured |
| SWE-bench Verified (Vals AI) | 7.8% | Not measured | Only Command A measured |
| Terminal-Bench 2.1 (Vals AI) | 17.6% | Not measured | Only Command A measured |
| LiveCodeBench (Artificial Analysis run) | 28.7% | 11.6% | Command A |
| SciCode | 38.5% | Not measured | Only Command A measured |
| Terminal-Bench Hard (Artificial Analysis run) | 25.0% | 0.8% | Command A |
| WeirdML | Not measured | 1.7% | Only Llama 3.1 8B Instruct measured |
| LMArena Text: coding | 1330 | 1195 | Command A |
| LMArena Text: software and IT | 1336 | 1195 | Command A |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Command A | Llama 3.1 8B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 6.9 | Command A |
| Epoch Capabilities Index | Not measured | 116.5 | Only Llama 3.1 8B Instruct measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Command A | Llama 3.1 8B Instruct | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | Not measured | Only Command A measured |
| Finance Agent (Vals AI) | 9.0% | Not measured | Only Command A measured |
| τ²-Bench Telecom | 80.7% | 16.4% | Command A |
| BALROG | Not measured | 15.1% | Only Llama 3.1 8B Instruct measured |
| Berkeley Function Calling Leaderboard (BFCL) | 46.5% | 25.8% | Command A |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Command A | Llama 3.1 8B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond | 48.5% | Not measured | Only Command A measured |
| GPQA Diamond (Artificial Analysis run) | 76.1% | 25.9% | Command A |
| Humanity's Last Exam (Artificial Analysis run) | 12.0% | 5.3% | Command A |
| GPQA Diamond (Epoch AI run) | Not measured | 27.0% | Only Llama 3.1 8B Instruct measured |
| LMArena Text: hard prompts | 1326 | 1175 | Command A |
| LMArena Text: expert | 1296 | 1144 | Command A |
| LMArena Text: hard prompts in English | 1335 | 1196 | Command A |
| Kagi LLM Benchmark | 28.8% | Not measured | Only Command A measured |
| Neither model has a result on the other 14 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Command A | Llama 3.1 8B Instruct | Leader |
|---|---|---|---|
| AIME | 13.3% | Not measured | Only Command A measured |
| MATH 500 (Vals AI) | 76.2% | Not measured | Only Command A measured |
| MGSM (Vals AI) | 85.7% | Not measured | Only Command A measured |
| AA Math Index | 13.0 | 4.3 | Command A |
| AIME 2025 (Artificial Analysis run) | 13.0% | 4.3% | Command A |
| OTIS Mock AIME | Not measured | 1.7% | Only Llama 3.1 8B Instruct measured |
| MATH level 5 | Not measured | 22.9% | Only Llama 3.1 8B Instruct measured |
| GSM8K | Not measured | 82.4% | Only Llama 3.1 8B Instruct measured |
| LMArena Text: math | 1300 | 1179 | Command A |
| LMArena Text: mathematical work | 1312 | 1180 | Command A |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Command A | Llama 3.1 8B Instruct | Leader |
|---|---|---|---|
| MMLU Pro | 69.2% | Not measured | Only Command A measured |
| LegalBench (Vals AI) | 79.7% | Not measured | Only Command A measured |
| CaseLaw (Vals AI) | 64.5% | Not measured | Only Command A measured |
| CorpFin (Vals AI) | 46.0% | Not measured | Only Command A measured |
| TaxEval (Vals AI) | 61.4% | Not measured | Only Command A measured |
| MedQA (Vals AI) | 80.5% | Not measured | Only Command A measured |
| MedCode (Vals AI) | 19.7% | Not measured | Only Command A measured |
| MMLU Pro (Artificial Analysis run) | 71.2% | 47.6% | Command A |
| MMLU | Not measured | 56.1% | Only Llama 3.1 8B Instruct measured |
| LMArena Text: science | 1339 | 1193 | Command A |
| LMArena Text: medicine and healthcare | 1334 | 1182 | Command A |
| LMArena Text: legal and government | 1348 | 1206 | Command A |
| LMArena Text: business and finance | 1315 | 1166 | Command A |
| Neither model has a result on the other 5 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command A | Llama 3.1 8B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index200
| Benchmark | Command A | Llama 3.1 8B Instruct | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 55.7% | Not measured | Only Command A measured |
| IFBench | 73.9% | 28.6% | Command A |
| Long context reasoning (AA-LCR) | 52.7% | 18.0% | Command A |
| DTBench | 61.3% | 50.9% | Command A |
| LMCA | 10.3% | 5.4% | Command A |
| PIQA | Not measured | 81.2% | Only Llama 3.1 8B Instruct measured |
| LMArena Text | 1331 | 1187 | Command A |
| LMArena Text: instruction following | 1309 | 1159 | Command A |
| LMArena Text: creative writing | 1319 | 1154 | Command A |
| LMArena Text: English | 1344 | 1218 | Command A |
| LMArena Text: non-English | 1313 | 1148 | Command A |
| LMArena Text: Chinese | 1327 | 1151 | Command A |
| LMArena Text: German | 1342 | 1144 | Command A |
| LMArena Text: Japanese | 1285 | 1061 | Command A |
| LMArena Text: Korean | 1285 | 1053 | Command A |
| LMArena Text: French | 1351 | 1178 | Command A |
| LMArena Text: Spanish | 1347 | 1169 | Command A |
| LMArena Text: Russian | 1314 | 1158 | Command A |
| LMArena Text: Polish | 1324 | Not measured | Only Command A measured |
| LMArena Text: multi-turn | 1338 | 1172 | Command A |
| LMArena Text: longer queries | 1334 | 1181 | Command A |
| LMArena Text: writing and language | 1328 | 1162 | Command A |
| LMArena Text: entertainment and media | 1306 | 1145 | Command A |
| Neither model has a result on the other 23 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command A | Llama 3.1 8B Instruct | 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 | Cohere Command A | Meta Llama 3.1 8B Instruct |
|---|---|---|
| Maker | Cohere | Meta Llama |
| Weights | Open weights | Open weights |
| Released | March 13, 2025 | July 23, 2024 |
| Context window | 256K | 131K |
| Input $/Mtok | $2.50 | $0.05 |
| Output $/Mtok | $10.00 | $0.08 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $2.69 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Command A better than Llama 3.1 8B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Command A for a larger context window (256K against 131K tokens).
Which is cheaper, Command A or Llama 3.1 8B Instruct?
Command A costs $2.50 per million input tokens and $10.00 per million output tokens; Llama 3.1 8B Instruct costs $0.05 and $0.08. Cost per solved task is known for Command A only.
Which has the bigger context window, Command A or Llama 3.1 8B Instruct?
Command A, with 256K tokens against 131K.
How many benchmarks is the Command A vs Llama 3.1 8B Instruct comparison based on?
42 benchmarks have a result for both models as of October 21, 2026. Command A's coding index rests on 1 independent benchmark and Llama 3.1 8B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.