Kimi K3 vs Llama 3.2 3B Instruct
Updated October 21, 2026. 27 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Only Kimi K3 has a coding score, 62.3 on the Vibe Coding Index; Llama 3.2 3B Instruct has none, so the two cannot be ranked on coding.
Llama 3.2 3B Instruct has the edge where output tokens cost 45.1x less.
- Shared results
- 27
- Kimi K3 only
- 90
- Llama 3.2 3B Instruct only
- 7
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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 Kimi K3 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Kimi K3
Kimi K3 leads, 43.6 against 5.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Kimi K3 has a AA Agentic Index result, 50.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Kimi K3 has a GPQA Diamond result, 92.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K3 has a MMLU Pro result, 88.0%.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K3 has a Design Arena: websites result, 1335.
Directional only
General
Vals Index
No call
Only Kimi K3 has a Vals Index result, 53.0%.
Directional only
Long documents
Listed context window
Kimi K3
Kimi K3 takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.2 3B Instruct
Kimi K3 $0.011, Llama 3.2 3B Instruct $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Kimi K3 has the number, $0.81.
Directional only
At a glance
- Coding index
- Kimi K3 62.3 from 6 benchmarks, Llama 3.2 3B Instruct not benchmarked.
- Widest category
- General, 68.4 points apart on average over 13 shared benchmarks.
- Widest single gap
- LMArena Text: Chinese: Kimi K3 1529 against Llama 3.2 3B Instruct 1017, 85.2 points apart on a 0 to 100 scale.
- Output price
- Kimi K3 $15.00 against Llama 3.2 3B Instruct $0.3325 per million output tokens, 45.1x apart.
- Context window
- Kimi K3 takes 1.05M tokens, Llama 3.2 3B 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 | Kimi K3 | Bars | Llama 3.2 3B Instruct | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 13 | 0 | ||
| All shared boards | 27 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Kimi K3 | Llama 3.2 3B Instruct | Leader |
|---|---|---|---|
| LiveBench coding | 59.3% | Not measured | Only Kimi K3 measured |
| LMArena WebDev | 1655 | Not measured | Only Kimi K3 measured |
| AA Coding Index | 76.2 | Not measured | Only Kimi K3 measured |
| LiveCodeBench (Vals AI) | 87.2% | Not measured | Only Kimi K3 measured |
| SWE-bench Verified (Vals AI) | 93.4% | Not measured | Only Kimi K3 measured |
| Terminal-Bench 4 (Vals AI) | 17.2% | Not measured | Only Kimi K3 measured |
| Vibe Code Bench (Vals AI) | 85.0% | Not measured | Only Kimi K3 measured |
| Code migration (Vals AI) | 16.1% | Not measured | Only Kimi K3 measured |
| ProgramBench (Vals AI) | 2.0% | Not measured | Only Kimi K3 measured |
| IOI (Vals AI) | 48.9% | Not measured | Only Kimi K3 measured |
| Terminal-Bench 2.1 (Vals AI) | 80.9% | Not measured | Only Kimi K3 measured |
| SWE-bench Multimodal (Vals AI) | 44.2% | Not measured | Only Kimi K3 measured |
| Vibe Code Bench 1-100 (Vals AI) | 18.2% | Not measured | Only Kimi K3 measured |
| CyberBench (Vals AI) | 75.2% | Not measured | Only Kimi K3 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 8.3% | Only Llama 3.2 3B Instruct measured |
| SciCode | 59.5% | Not measured | Only Kimi K3 measured |
| FrontierCode | 44.2% | Not measured | Only Kimi K3 measured |
| FrontierSWE | 25.9% | Not measured | Only Kimi K3 measured |
| WeirdML | 82.6% | Not measured | Only Kimi K3 measured |
| ALE-Bench | 1524.5 | Not measured | Only Kimi K3 measured |
| LMArena Text: coding | 1508 | 1098 | Kimi K3 |
| LMArena Text: software and IT | 1499 | 1103 | Kimi K3 |
| LMArena WebDev: React | 1670 | Not measured | Only Kimi K3 measured |
| LMArena WebDev: HTML | 1644 | Not measured | Only Kimi K3 measured |
| LMArena WebDev: from an image | 1579 | Not measured | Only Kimi K3 measured |
| Neither model has a result on the other 13 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K3 | Llama 3.2 3B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 43.6 | 5.7 | Kimi K3 |
| Epoch Capabilities Index | 157.9 | Not measured | Only Kimi K3 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index26 boards, none shared
| Benchmark | Kimi K3 | Llama 3.2 3B Instruct | Leader |
|---|---|---|---|
| AA Agentic Index | 50.0 | Not measured | Only Kimi K3 measured |
| Design Arena: agents building web apps | 1295 | Not measured | Only Kimi K3 measured |
| Design Arena: agents building full-stack apps | 1315 | Not measured | Only Kimi K3 measured |
| Design Arena: agents building mobile apps | 1268 | Not measured | Only Kimi K3 measured |
| Design Arena: agents building Android apps | 1256 | Not measured | Only Kimi K3 measured |
| Design Arena: agents building Godot games | 1223 | Not measured | Only Kimi K3 measured |
| Design Arena: agents building games | 1252 | Not measured | Only Kimi K3 measured |
| Design Arena: HTML slides | 1256 | Not measured | Only Kimi K3 measured |
| Design Arena: PowerPoint slides | 1273 | Not measured | Only Kimi K3 measured |
| Design Arena: spreadsheets | 1054 | Not measured | Only Kimi K3 measured |
| LiveBench research | 79.0% | Not measured | Only Kimi K3 measured |
| LiveBench browser | 16.0% | Not measured | Only Kimi K3 measured |
| LiveBench long agentic | 42.8% | Not measured | Only Kimi K3 measured |
| Finance Agent (Vals AI) | 53.1% | Not measured | Only Kimi K3 measured |
| Tax Agent Bench (Vals AI) | 33.4% | Not measured | Only Kimi K3 measured |
| Legal Research Bench (Vals AI) | 46.1% | Not measured | Only Kimi K3 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 12.9% | Not measured | Only Kimi K3 measured |
| Excel Modeling Benchmark (Vals AI) | 66.7% | Not measured | Only Kimi K3 measured |
| BioMysteryBench (Vals AI) | 72.6% | Not measured | Only Kimi K3 measured |
| Terminal-Bench-Science (Vals AI) | 1.4% | Not measured | Only Kimi K3 measured |
| Time Horizon Index (Vals AI) | 10.5% | Not measured | Only Kimi K3 measured |
| τ²-Bench Telecom | Not measured | 21.1% | Only Llama 3.2 3B Instruct measured |
| APEX-Agents | 47.8% | Not measured | Only Kimi K3 measured |
| BALROG | Not measured | 10.1% | Only Llama 3.2 3B Instruct measured |
| PostTrainBench | 32.0% | Not measured | Only Kimi K3 measured |
| Vending-Bench 2 | $5,165 | Not measured | Only Kimi K3 measured |
| Neither model has a result on the other 13 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Kimi K3 | Llama 3.2 3B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond | 92.9% | Not measured | Only Kimi K3 measured |
| LiveBench reasoning | 90.7% | Not measured | Only Kimi K3 measured |
| MMMU Pro (Vals AI) | 88.2% | Not measured | Only Kimi K3 measured |
| GPQA Diamond (Artificial Analysis run) | 93.5% | 25.5% | Kimi K3 |
| Humanity's Last Exam (Artificial Analysis run) | 46.9% | 5.3% | Kimi K3 |
| GPQA Diamond (Epoch AI run) | 93.1% | Not measured | Only Kimi K3 measured |
| ARC-AGI | 94.5% | Not measured | Only Kimi K3 measured |
| ARC-AGI-2 | 60.4% | Not measured | Only Kimi K3 measured |
| SimpleBench | 60.7% | Not measured | Only Kimi K3 measured |
| Chess puzzles | 37.0% | Not measured | Only Kimi K3 measured |
| Mystery game puzzles | 26.0% | Not measured | Only Kimi K3 measured |
| LMArena Text: hard prompts | 1495 | 1095 | Kimi K3 |
| LMArena Text: expert | 1520 | 1090 | Kimi K3 |
| LMArena Text: hard prompts in English | 1496 | 1141 | Kimi K3 |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K3 | Llama 3.2 3B Instruct | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 3.3 | Only Llama 3.2 3B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 3.3% | Only Llama 3.2 3B Instruct measured |
| OTIS Mock AIME | 97.2% | Not measured | Only Kimi K3 measured |
| FrontierMath, tiers 1 to 3 | 72.2% | Not measured | Only Kimi K3 measured |
| FrontierMath, tier 4 | 39.0% | Not measured | Only Kimi K3 measured |
| ProofBench | 87.0% | Not measured | Only Kimi K3 measured |
| LMArena Text: math | 1494 | 1126 | Kimi K3 |
| LMArena Text: mathematical work | 1505 | 1128 | Kimi K3 |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Kimi K3 | Llama 3.2 3B Instruct | Leader |
|---|---|---|---|
| MMLU Pro | 88.0% | Not measured | Only Kimi K3 measured |
| LegalBench (Vals AI) | 86.2% | Not measured | Only Kimi K3 measured |
| CorpFin (Vals AI) | 71.6% | Not measured | Only Kimi K3 measured |
| TaxEval (Vals AI) | 75.7% | Not measured | Only Kimi K3 measured |
| MortgageTax (Vals AI) | 66.3% | Not measured | Only Kimi K3 measured |
| MedCode (Vals AI) | 49.4% | Not measured | Only Kimi K3 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 34.7% | Only Llama 3.2 3B Instruct measured |
| SimpleQA Verified | 50.6% | Not measured | Only Kimi K3 measured |
| LMArena Text: science | 1508 | 1106 | Kimi K3 |
| LMArena Text: medicine and healthcare | 1489 | 1104 | Kimi K3 |
| LMArena Text: legal and government | 1503 | 1115 | Kimi K3 |
| LMArena Text: business and finance | 1470 | 1074 | Kimi K3 |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Kimi K3 | Llama 3.2 3B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1335 | Not measured | Only Kimi K3 measured |
| Design Arena: UI components | 1344 | Not measured | Only Kimi K3 measured |
| Design Arena: game dev | 1360 | Not measured | Only Kimi K3 measured |
| Design Arena: data viz | 1350 | Not measured | Only Kimi K3 measured |
| Design Arena: 3D | 1388 | Not measured | Only Kimi K3 measured |
| Design Arena: all code categories | 1361 | Not measured | Only Kimi K3 measured |
| Design Arena: SVG | 1302 | Not measured | Only Kimi K3 measured |
| LiveBench design | 77.2% | Not measured | Only Kimi K3 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index130
| Benchmark | Kimi K3 | Llama 3.2 3B Instruct | Leader |
|---|---|---|---|
| Vals Index | 53.0% | Not measured | Only Kimi K3 measured |
| LiveBench data analysis | 78.7% | Not measured | Only Kimi K3 measured |
| Public Benefits Bench (Vals AI) | 68.2% | Not measured | Only Kimi K3 measured |
| SAGE (Vals AI) | 52.8% | Not measured | Only Kimi K3 measured |
| MedScribe (Vals AI) | 88.0% | Not measured | Only Kimi K3 measured |
| Vals Multimodal Index | 73.4% | Not measured | Only Kimi K3 measured |
| IFBench | Not measured | 26.2% | Only Llama 3.2 3B Instruct measured |
| Long context reasoning (AA-LCR) | 88.7% | 4.3% | Kimi K3 |
| DTBench | 91.2% | Not measured | Only Kimi K3 measured |
| LMCA | 52.7% | Not measured | Only Kimi K3 measured |
| Surface Evolver Bench | 95.0% | Not measured | Only Kimi K3 measured |
| Furniture assembly | 34.2% | Not measured | Only Kimi K3 measured |
| LMArena Text | 1476 | 1110 | Kimi K3 |
| LMArena Text: instruction following | 1485 | 1089 | Kimi K3 |
| LMArena Text: creative writing | 1457 | 1094 | Kimi K3 |
| LMArena Text: English | 1481 | 1180 | Kimi K3 |
| LMArena Text: non-English | 1466 | 1019 | Kimi K3 |
| LMArena Text: Chinese | 1529 | 1017 | Kimi K3 |
| LMArena Text: German | 1490 | 1056 | Kimi K3 |
| LMArena Text: Japanese | 1494 | Not measured | Only Kimi K3 measured |
| LMArena Text: Korean | 1460 | Not measured | Only Kimi K3 measured |
| LMArena Text: French | 1492 | Not measured | Only Kimi K3 measured |
| LMArena Text: Spanish | 1472 | Not measured | Only Kimi K3 measured |
| LMArena Text: Russian | 1485 | 949 | Kimi K3 |
| LMArena Text: Polish | 1458 | Not measured | Only Kimi K3 measured |
| LMArena Text: multi-turn | 1489 | 1105 | Kimi K3 |
| LMArena Text: longer queries | 1494 | 1100 | Kimi K3 |
| LMArena Text: writing and language | 1471 | 1096 | Kimi K3 |
| LMArena Text: entertainment and media | 1453 | 1083 | Kimi K3 |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Kimi K3 | Llama 3.2 3B 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 3.2 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 | MoonshotAI Kimi K3 | Meta Llama 3.2 3B Instruct |
|---|---|---|
| Maker | Moonshot AI | Meta Llama |
| Weights | Open weights | Open weights |
| Released | July 16, 2026 | September 25, 2024 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $3.00 | $0.0505 |
| Output $/Mtok | $15.00 | $0.3325 |
| Coding index | 62.3 | Not benchmarked |
| Independent measurements behind it | 6 | 0 |
| Cost per solved task | $0.81 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K3 better than Llama 3.2 3B Instruct for coding?
Only Kimi K3 has a coding score, 62.3 on the Vibe Coding Index; Llama 3.2 3B Instruct has none, so the two cannot be ranked on coding. Llama 3.2 3B Instruct has the edge where output tokens cost 45.1x less.
Which is cheaper, Kimi K3 or Llama 3.2 3B Instruct?
Kimi K3 costs $3.00 per million input tokens and $15.00 per million output tokens; Llama 3.2 3B Instruct costs $0.0505 and $0.3325. Cost per solved task is known for Kimi K3 only.
Which has the bigger context window, Kimi K3 or Llama 3.2 3B Instruct?
Kimi K3, with 1.05M tokens against 131K.
How many benchmarks is the Kimi K3 vs Llama 3.2 3B Instruct comparison based on?
27 benchmarks have a result for both models as of October 21, 2026. Kimi K3's coding index rests on 6 independent benchmarks and Llama 3.2 3B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.