Llama 3.3 70B Instruct vs Muse Spark 1.2
Muse Spark 1.2 leads Llama 3.3 70B Instruct on the Artificial Analysis Intelligence Index, 39.6 to 7.7, and Llama 3.3 70B Instruct costs 5.9x less per output token ($0.72 vs $4.25 per million). Updated October 22, 2026; 35 benchmarks have a result for both.
Llama 3.3 70B Instruct or Muse Spark 1.2: which to pick
Only Muse Spark 1.2 has a coding score, 55.7 on the Vibe Coding Index; Llama 3.3 70B Instruct has none, so the two cannot be ranked on coding.
Pick Llama 3.3 70B Instruct for output tokens 5.9x cheaper ($0.72 vs $4.25 per million).
- Shared results
- 35
- Llama 3.3 70B Instruct only
- 17
- Muse Spark 1.2 only
- 62
- 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
Only Muse Spark 1.2 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Muse Spark 1.2
Muse Spark 1.2 leads, 39.6 against 7.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Muse Spark 1.2 has a AA Agentic Index result, 43.2.
Directional only
Knowledge
MMLU Pro
No call
Only Muse Spark 1.2 has a MMLU Pro result, 88.3%.
Directional only
Web design
Design Arena: websites
No call
Only Muse Spark 1.2 has a Design Arena: websites result, 1312.
Directional only
Long documents
Listed context window
Muse Spark 1.2
Muse Spark 1.2 takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.3 70B Instruct
Llama 3.3 70B Instruct $0.0008, Muse Spark 1.2 $0.0034 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Muse Spark 1.2 has the number, $0.64.
Directional only
At a glance
- Coding index
- Llama 3.3 70B Instruct not benchmarked, Muse Spark 1.2 55.7 from 5 benchmarks.
- Widest category
- Coding, 46.1 points apart on average over 4 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): Llama 3.3 70B Instruct 15.7% against Muse Spark 1.2 79.0%, 63.3 points apart on a 0 to 100 scale.
- Output price
- Llama 3.3 70B Instruct $0.72 against Muse Spark 1.2 $4.25 per million output tokens, 5.9x apart.
- Context window
- Llama 3.3 70B Instruct takes 131K tokens, Muse Spark 1.2 1.05M.
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 3.3 70B Instruct | Bars | Muse Spark 1.2 | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 0 | 6 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 17 | ||
| All shared boards | 0 | 35 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
| Benchmark | Llama 3.3 70B Instruct | Muse Spark 1.2 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 78.2% | Only Muse Spark 1.2 measured |
| LMArena WebDev | Not measured | 1534 | Only Muse Spark 1.2 measured |
| AA Coding Index | 11.9 | 72.2 | Muse Spark 1.2 |
| SWE-bench Verified (Vals AI) | Not measured | 86.6% | Only Muse Spark 1.2 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 6.1% | Only Muse Spark 1.2 measured |
| Vibe Code Bench (Vals AI) | Not measured | 79.1% | Only Muse Spark 1.2 measured |
| Code migration (Vals AI) | Not measured | 29.9% | Only Muse Spark 1.2 measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only Muse Spark 1.2 measured |
| IOI (Vals AI) | Not measured | 21.8% | Only Muse Spark 1.2 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 69.7% | Only Muse Spark 1.2 measured |
| SkillsBench (Vals AI) | Not measured | 53.0% | Only Muse Spark 1.2 measured |
| CyberBench (Vals AI) | Not measured | 69.5% | Only Muse Spark 1.2 measured |
| LiveCodeBench (Artificial Analysis run) | 28.8% | Not measured | Only Llama 3.3 70B Instruct measured |
| SciCode | Not measured | 57.4% | Only Muse Spark 1.2 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 3.0% | Not measured | Only Llama 3.3 70B Instruct measured |
| FrontierSWE | Not measured | 12.0% | Only Muse Spark 1.2 measured |
| WeirdML | 14.4% | 60.3% | Muse Spark 1.2 |
| LMArena Text: coding | 1268 | 1505 | Muse Spark 1.2 |
| LMArena Text: software and IT | 1273 | 1505 | Muse Spark 1.2 |
| LMArena WebDev: React | Not measured | 1526 | Only Muse Spark 1.2 measured |
| LMArena WebDev: HTML | Not measured | 1543 | Only Muse Spark 1.2 measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Llama 3.3 70B Instruct | Muse Spark 1.2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.7 | 39.6 | Muse Spark 1.2 |
| Epoch Capabilities Index | 127.3 | 155.1 | Muse Spark 1.2 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
| Benchmark | Llama 3.3 70B Instruct | Muse Spark 1.2 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 43.2 | Only Muse Spark 1.2 measured |
| Design Arena: agents building web apps | Not measured | 1221 | Only Muse Spark 1.2 measured |
| Design Arena: agents building full-stack apps | Not measured | 1210 | Only Muse Spark 1.2 measured |
| Design Arena: agents building mobile apps | Not measured | 1181 | Only Muse Spark 1.2 measured |
| Design Arena: agents building Android apps | Not measured | 1222 | Only Muse Spark 1.2 measured |
| Design Arena: agents building games | Not measured | 1179 | Only Muse Spark 1.2 measured |
| Design Arena: HTML slides | Not measured | 1085 | Only Muse Spark 1.2 measured |
| Design Arena: PowerPoint slides | Not measured | 1172 | Only Muse Spark 1.2 measured |
| LiveBench research | Not measured | 67.7% | Only Muse Spark 1.2 measured |
| LiveBench browser | Not measured | 36.0% | Only Muse Spark 1.2 measured |
| LiveBench long agentic | Not measured | 21.3% | Only Muse Spark 1.2 measured |
| SREBench (Vals AI) | Not measured | 0.0% | Only Muse Spark 1.2 measured |
| Finance Agent (Vals AI) | Not measured | 60.6% | Only Muse Spark 1.2 measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.8% | Only Muse Spark 1.2 measured |
| Legal Research Bench (Vals AI) | Not measured | 43.8% | Only Muse Spark 1.2 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 57.0% | Only Muse Spark 1.2 measured |
| BioMysteryBench (Vals AI) | Not measured | 64.8% | Only Muse Spark 1.2 measured |
| τ²-Bench Telecom | 26.6% | Not measured | Only Llama 3.3 70B Instruct measured |
| APEX-Agents | Not measured | 45.4% | Only Muse Spark 1.2 measured |
| BALROG | 23.0% | Not measured | Only Llama 3.3 70B Instruct measured |
| Berkeley Function Calling Leaderboard (BFCL) | 31.9% | Not measured | Only Llama 3.3 70B Instruct measured |
| Neither model has a result on the other 20 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Llama 3.3 70B Instruct | Muse Spark 1.2 | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 90.0% | Only Muse Spark 1.2 measured |
| MMMU Pro (Vals AI) | Not measured | 86.1% | Only Muse Spark 1.2 measured |
| GPQA Diamond (Artificial Analysis run) | 49.8% | 90.4% | Muse Spark 1.2 |
| Humanity's Last Exam (Artificial Analysis run) | 3.6% | 45.5% | Muse Spark 1.2 |
| GPQA Diamond (Epoch AI run) | 47.4% | Not measured | Only Llama 3.3 70B Instruct measured |
| SimpleBench | 19.9% | 74.5% | Muse Spark 1.2 |
| Chess puzzles | Not measured | 27.0% | Only Muse Spark 1.2 measured |
| LMArena Text: hard prompts | 1257 | 1489 | Muse Spark 1.2 |
| LMArena Text: expert | 1225 | 1475 | Muse Spark 1.2 |
| LMArena Text: hard prompts in English | 1277 | 1487 | Muse Spark 1.2 |
| LMArena Vision: diagrams | Not measured | 1317 | Only Muse Spark 1.2 measured |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Llama 3.3 70B Instruct | Muse Spark 1.2 | Leader |
|---|---|---|---|
| AA Math Index | 7.7 | Not measured | Only Llama 3.3 70B Instruct measured |
| AIME 2025 (Artificial Analysis run) | 7.7% | Not measured | Only Llama 3.3 70B Instruct measured |
| OTIS Mock AIME | 5.1% | Not measured | Only Llama 3.3 70B Instruct measured |
| ProofBench | Not measured | 43.0% | Only Muse Spark 1.2 measured |
| MATH level 5 | 41.6% | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: math | 1267 | 1484 | Muse Spark 1.2 |
| LMArena Text: mathematical work | 1267 | 1480 | Muse Spark 1.2 |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Llama 3.3 70B Instruct | Muse Spark 1.2 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 88.3% | Only Muse Spark 1.2 measured |
| LegalBench (Vals AI) | Not measured | 85.3% | Only Muse Spark 1.2 measured |
| CorpFin (Vals AI) | Not measured | 70.9% | Only Muse Spark 1.2 measured |
| TaxEval (Vals AI) | Not measured | 80.4% | Only Muse Spark 1.2 measured |
| MortgageTax (Vals AI) | Not measured | 65.4% | Only Muse Spark 1.2 measured |
| MedCode (Vals AI) | Not measured | 49.4% | Only Muse Spark 1.2 measured |
| MMLU Pro (Artificial Analysis run) | 71.3% | Not measured | Only Llama 3.3 70B Instruct measured |
| SimpleQA Verified | Not measured | 60.3% | Only Muse Spark 1.2 measured |
| MMLU | 86.3% | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: science | 1284 | 1500 | Muse Spark 1.2 |
| LMArena Text: medicine and healthcare | 1275 | 1496 | Muse Spark 1.2 |
| LMArena Text: legal and government | 1284 | 1517 | Muse Spark 1.2 |
| LMArena Text: business and finance | 1243 | 1484 | Muse Spark 1.2 |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Llama 3.3 70B Instruct | Muse Spark 1.2 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1312 | Only Muse Spark 1.2 measured |
| Design Arena: UI components | Not measured | 1298 | Only Muse Spark 1.2 measured |
| Design Arena: game dev | Not measured | 1301 | Only Muse Spark 1.2 measured |
| Design Arena: data viz | Not measured | 1334 | Only Muse Spark 1.2 measured |
| Design Arena: 3D | Not measured | 1301 | Only Muse Spark 1.2 measured |
| Design Arena: all code categories | Not measured | 1312 | Only Muse Spark 1.2 measured |
| Design Arena: SVG | Not measured | 1284 | Only Muse Spark 1.2 measured |
| Design Arena: ASCII art | Not measured | 1284 | Only Muse Spark 1.2 measured |
| LiveBench design | Not measured | 67.1% | Only Muse Spark 1.2 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
| Benchmark | Llama 3.3 70B Instruct | Muse Spark 1.2 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 76.5% | Only Muse Spark 1.2 measured |
| Public Benefits Bench (Vals AI) | Not measured | 68.5% | Only Muse Spark 1.2 measured |
| SAGE (Vals AI) | Not measured | 47.7% | Only Muse Spark 1.2 measured |
| MedScribe (Vals AI) | Not measured | 90.1% | Only Muse Spark 1.2 measured |
| Vals Multimodal Index | Not measured | 69.8% | Only Muse Spark 1.2 measured |
| IFBench | 47.1% | Not measured | Only Llama 3.3 70B Instruct measured |
| Long context reasoning (AA-LCR) | 15.7% | 79.0% | Muse Spark 1.2 |
| DTBench | 59.5% | 94.7% | Muse Spark 1.2 |
| LMCA | 17.5% | 48.4% | Muse Spark 1.2 |
| Fiction.LiveBench | 33.3% | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text | 1274 | 1482 | Muse Spark 1.2 |
| LMArena Text: instruction following | 1242 | 1462 | Muse Spark 1.2 |
| LMArena Text: creative writing | 1250 | 1436 | Muse Spark 1.2 |
| LMArena Vision | Not measured | 1304 | Only Muse Spark 1.2 measured |
| LMArena Text: English | 1303 | 1483 | Muse Spark 1.2 |
| LMArena Text: non-English | 1236 | 1476 | Muse Spark 1.2 |
| LMArena Text: Chinese | 1217 | 1509 | Muse Spark 1.2 |
| LMArena Text: German | 1251 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: Japanese | 1150 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: Korean | 1142 | 1462 | Muse Spark 1.2 |
| LMArena Text: French | 1282 | 1495 | Muse Spark 1.2 |
| LMArena Text: Spanish | 1269 | 1484 | Muse Spark 1.2 |
| LMArena Text: Russian | 1252 | 1483 | Muse Spark 1.2 |
| LMArena Text: Polish | 1259 | Not measured | Only Llama 3.3 70B Instruct measured |
| LMArena Text: multi-turn | 1280 | 1502 | Muse Spark 1.2 |
| LMArena Text: longer queries | 1255 | 1473 | Muse Spark 1.2 |
| LMArena Text: writing and language | 1255 | 1453 | Muse Spark 1.2 |
| LMArena Text: entertainment and media | 1241 | 1443 | Muse Spark 1.2 |
| LMArena Vision: English | Not measured | 1291 | Only Muse Spark 1.2 measured |
| LMArena Vision: reading text | Not measured | 1313 | Only Muse Spark 1.2 measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Llama 3.3 70B Instruct | Muse Spark 1.2 | 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 3.3 70B Instruct costs less
Repository review
50K input + 3K output tokens
Llama 3.3 70B Instruct costs less
Agent loop
200K input + 10K output tokens
Llama 3.3 70B 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 3.3 70B Instruct | Meta Muse Spark 1.2 |
|---|---|---|
| Maker | Meta Llama | Meta |
| Weights | Open weights | No public weights listed |
| Released | December 6, 2024 | August 5, 2026 |
| Context window | 131K | 1.05M |
| Input $/Mtok | $0.45 | $1.25 |
| Output $/Mtok | $0.72 | $4.25 |
| Coding index | Not benchmarked | 55.7 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | $0.64 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Llama 3.3 70B Instruct better than Muse Spark 1.2 for coding?
Only Muse Spark 1.2 has a coding score, 55.7 on the Vibe Coding Index; Llama 3.3 70B Instruct has none, so the two cannot be ranked on coding. Pick Llama 3.3 70B Instruct for output tokens 5.9x cheaper ($0.72 vs $4.25 per million).
Which is cheaper, Llama 3.3 70B Instruct or Muse Spark 1.2?
Llama 3.3 70B Instruct costs $0.45 per million input tokens and $0.72 per million output tokens; Muse Spark 1.2 costs $1.25 and $4.25. Cost per solved task is known for Muse Spark 1.2 only.
Which has the bigger context window, Llama 3.3 70B Instruct or Muse Spark 1.2?
Muse Spark 1.2, with 1.05M tokens against 131K.
How many benchmarks is the Llama 3.3 70B Instruct vs Muse Spark 1.2 comparison based on?
35 benchmarks have a result for both models as of October 22, 2026. Llama 3.3 70B Instruct's coding index rests on 0 independent benchmarks and Muse Spark 1.2's on 5. Where only one model has a result, the page says so instead of naming a winner.