Llama 3.2 3B Instruct vs Muse Spark Open
Llama 3.2 3B Instruct costs 12.8x less per output token than Muse Spark Open ($0.3325 vs $4.25 per million). Updated October 21, 2026; 3 benchmarks have a result for both.
Llama 3.2 3B Instruct or Muse Spark Open: which to pick
Only Muse Spark Open has a coding score, 47.4 on the Vibe Coding Index; Llama 3.2 3B Instruct has none, so the two cannot be ranked on coding.
Pick Llama 3.2 3B Instruct for output tokens 12.8x cheaper ($0.3325 vs $4.25 per million).
- Shared results
- 3
- Llama 3.2 3B Instruct only
- 32
- Muse Spark Open only
- 25
- Like-for-like categories
- 2 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 Open has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Llama 3.2 3B Instruct has a AA Intelligence Index result, 5.7.
Directional only
Web design
Design Arena: websites
No call
Only Muse Spark Open has a Design Arena: websites result, 1317.
Directional only
General
Vals Index
No call
Only Muse Spark Open has a Vals Index result, 48.6%.
Directional only
Long documents
Listed context window
Muse Spark Open
Muse Spark Open takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.2 3B Instruct
Llama 3.2 3B Instruct $0.0002, Muse Spark Open $0.0034 per turn.
List prices
At a glance
- Coding index
- Llama 3.2 3B Instruct not benchmarked, Muse Spark Open 47.4 from 4 benchmarks.
- Widest category
- General, 74.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Llama 3.2 3B Instruct 4.3% against Muse Spark Open 78.3%, 74.0 points apart on a 0 to 100 scale.
- Output price
- Llama 3.2 3B Instruct $0.3325 against Muse Spark Open $4.25 per million output tokens, 12.8x apart.
- Context window
- Llama 3.2 3B Instruct takes 131K tokens, Muse Spark Open 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 3.2 3B Instruct | Bars | Muse Spark Open | Ties |
|---|---|---|---|---|
| Reasoning | 0 | 2 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 3 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index12 boards, none shared
| Benchmark | Llama 3.2 3B Instruct | Muse Spark Open | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 73.6% | Only Muse Spark Open measured |
| LMArena WebDev | Not measured | 1528 | Only Muse Spark Open measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 6.6% | Only Muse Spark Open measured |
| Vibe Code Bench (Vals AI) | Not measured | 76.2% | Only Muse Spark Open measured |
| Code migration (Vals AI) | Not measured | 21.2% | Only Muse Spark Open measured |
| LiveCodeBench (Artificial Analysis run) | 8.3% | Not measured | Only Llama 3.2 3B Instruct measured |
| SciCode | Not measured | 58.4% | Only Muse Spark Open measured |
| ALE-Bench | Not measured | 1590.1 | Only Muse Spark Open measured |
| LMArena Text: coding | 1098 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: software and IT | 1103 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena WebDev: React | Not measured | 1529 | Only Muse Spark Open measured |
| LMArena WebDev: HTML | Not measured | 1495 | Only Muse Spark Open measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Llama 3.2 3B Instruct | Muse Spark Open | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.7 | Not measured | Only Llama 3.2 3B Instruct measured |
| Epoch Capabilities Index | Not measured | 155.1 | Only Muse Spark Open measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | Llama 3.2 3B Instruct | Muse Spark Open | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 80.3% | Only Muse Spark Open measured |
| LiveBench browser | Not measured | 36.0% | Only Muse Spark Open measured |
| LiveBench long agentic | Not measured | 18.9% | Only Muse Spark Open measured |
| Finance Agent (Vals AI) | Not measured | 61.3% | Only Muse Spark Open measured |
| Tax Agent Bench (Vals AI) | Not measured | 26.3% | Only Muse Spark Open measured |
| Legal Research Bench (Vals AI) | Not measured | 38.5% | Only Muse Spark Open measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 25.0% | Only Muse Spark Open measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 53.7% | Only Muse Spark Open measured |
| τ²-Bench Telecom | 21.1% | Not measured | Only Llama 3.2 3B Instruct measured |
| APEX-Agents | Not measured | 33.4% | Only Muse Spark Open measured |
| BALROG | 10.1% | Not measured | Only Llama 3.2 3B Instruct measured |
| Berkeley Function Calling Leaderboard (BFCL) | 21.9% | Not measured | Only Llama 3.2 3B Instruct measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Llama 3.2 3B Instruct | Muse Spark Open | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 73.7% | Only Muse Spark Open measured |
| GPQA Diamond (Artificial Analysis run) | 25.5% | 89.0% | Muse Spark Open |
| Humanity's Last Exam (Artificial Analysis run) | 5.3% | 43.9% | Muse Spark Open |
| LMArena Text: hard prompts | 1095 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: expert | 1090 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: hard prompts in English | 1141 | Not measured | Only Llama 3.2 3B Instruct measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Llama 3.2 3B Instruct | Muse Spark Open | Leader |
|---|---|---|---|
| AA Math Index | 3.3 | Not measured | Only Llama 3.2 3B Instruct measured |
| AIME 2025 (Artificial Analysis run) | 3.3% | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: math | 1126 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: mathematical work | 1128 | Not measured | Only Llama 3.2 3B Instruct measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Llama 3.2 3B Instruct | Muse Spark Open | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 34.7% | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: science | 1106 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: medicine and healthcare | 1104 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: legal and government | 1115 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: business and finance | 1074 | Not measured | Only Llama 3.2 3B Instruct measured |
| Neither model has a result on the other 13 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Llama 3.2 3B Instruct | Muse Spark Open | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1317 | Only Muse Spark Open measured |
| Design Arena: game dev | Not measured | 1294 | Only Muse Spark Open measured |
| LiveBench design | Not measured | 60.3% | Only Muse Spark Open measured |
| Neither model has a result on the other 6 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Llama 3.2 3B Instruct | Muse Spark Open | Leader |
|---|---|---|---|
| Vals Index | Not measured | 48.6% | Only Muse Spark Open measured |
| LiveBench data analysis | Not measured | 60.2% | Only Muse Spark Open measured |
| IFBench | 26.2% | Not measured | Only Llama 3.2 3B Instruct measured |
| Long context reasoning (AA-LCR) | 4.3% | 78.3% | Muse Spark Open |
| LMArena Text | 1110 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: instruction following | 1089 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: creative writing | 1094 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: English | 1180 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: non-English | 1019 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: Chinese | 1017 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: German | 1056 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: Russian | 949 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: multi-turn | 1105 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: longer queries | 1100 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: writing and language | 1096 | Not measured | Only Llama 3.2 3B Instruct measured |
| LMArena Text: entertainment and media | 1083 | Not measured | Only Llama 3.2 3B Instruct measured |
| Neither model has a result on the other 30 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Llama 3.2 3B Instruct | Muse Spark Open | 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 3.2 3B Instruct costs less
Repository review
50K input + 3K output tokens
Llama 3.2 3B Instruct costs less
Agent loop
200K input + 10K output tokens
Llama 3.2 3B 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 3.2 3B Instruct | Meta Muse Spark Open |
|---|---|---|
| Maker | Meta Llama | Meta |
| Weights | Open weights | Open weights |
| Released | September 25, 2024 | October 15, 2026 |
| Context window | 131K | 1.05M |
| Input $/Mtok | $0.0505 | $1.25 |
| Output $/Mtok | $0.3325 | $4.25 |
| Coding index | Not benchmarked | 47.4 |
| Independent measurements behind it | 0 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Llama 3.2 3B Instruct better than Muse Spark Open for coding?
Only Muse Spark Open has a coding score, 47.4 on the Vibe Coding Index; Llama 3.2 3B Instruct has none, so the two cannot be ranked on coding. Pick Llama 3.2 3B Instruct for output tokens 12.8x cheaper ($0.3325 vs $4.25 per million).
Which is cheaper, Llama 3.2 3B Instruct or Muse Spark Open?
Llama 3.2 3B Instruct costs $0.0505 per million input tokens and $0.3325 per million output tokens; Muse Spark Open costs $1.25 and $4.25. Cost per solved task is known for neither of them.
Which has the bigger context window, Llama 3.2 3B Instruct or Muse Spark Open?
Muse Spark Open, with 1.05M tokens against 131K.
How many benchmarks is the Llama 3.2 3B Instruct vs Muse Spark Open comparison based on?
3 benchmarks have a result for both models as of October 21, 2026. Llama 3.2 3B Instruct's coding index rests on 0 independent benchmarks and Muse Spark Open's on 4. Where only one model has a result, the page says so instead of naming a winner.