o3 vs Llama 3 8B Lunaris
Llama 3 8B Lunaris costs 160.0x less per output token than o3 ($0.05 vs $8.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- 51.1
- Output $/M
- $8.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.05
o3 or Llama 3 8B Lunaris: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick o3 for a larger context window (200K against 8K tokens).
No benchmark has tested both yet. o3 has results on Aider polyglot, SWE-bench Verified and SWE-bench Multimodal; Llama 3 8B Lunaris has none yet. Compare them on price and context instead.
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
No call
Only o3 has a AA Intelligence Index result, 20.2.
Directional only
Reasoning
GPQA Diamond
No call
Only o3 has a GPQA Diamond result, 84.1%.
Directional only
Math
AIME
No call
Only o3 has a AIME result, 85.3%.
Directional only
Knowledge
MMLU Pro
No call
Only o3 has a MMLU Pro result, 85.6%.
Directional only
Web design
Design Arena: websites
No call
Only o3 has a Design Arena: websites result, 1036.
Directional only
Long documents
Listed context window
o3
o3 takes 200K tokens against 8K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3 8B Lunaris
o3 $0.0060, Llama 3 8B Lunaris $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only o3 has the number, $0.571.
Directional only
At a glance
- Coding index
- o3 not benchmarked, Llama 3 8B Lunaris not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- o3 $8.00 against Llama 3 8B Lunaris $0.05 per million output tokens, 160.0x apart.
- Context window
- o3 takes 200K tokens, Llama 3 8B Lunaris 8K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index12 boards measured
| Benchmark | o3 | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| Aider polyglot | 81.3% | Not measured | Only o3 measured |
| SWE-bench Verified | 58.4% | Not measured | Only o3 measured |
| SWE-bench Multimodal | 36.0% | Not measured | Only o3 measured |
| LiveCodeBench (Vals AI) | 83.9% | Not measured | Only o3 measured |
| LiveCodeBench (Artificial Analysis run) | 80.8% | Not measured | Only o3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.1% | Not measured | Only o3 measured |
| GSO-Bench | 8.8% | Not measured | Only o3 measured |
| WeirdML | 52.4% | Not measured | Only o3 measured |
| ALE-Bench | 933.5 | Not measured | Only o3 measured |
| LMArena Text: coding | 1407 | Not measured | Only o3 measured |
| LMArena Text: software and IT | 1415 | Not measured | Only o3 measured |
| SciCode | 9.2% | Not measured | Only o3 measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | o3 | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.2 | Not measured | Only o3 measured |
| Epoch Capabilities Index | 146.7 | Not measured | Only o3 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | o3 | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 80.7% | Not measured | Only o3 measured |
| METR time horizons | 65.4% | Not measured | Only o3 measured |
| GDPval | 30.8% | Not measured | Only o3 measured |
| DeepResearch Bench | 45.2% | Not measured | Only o3 measured |
| OSWorld | 23.0% | Not measured | Only o3 measured |
| Berkeley Function Calling Leaderboard (BFCL) | 63.0% | Not measured | Only o3 measured |
| BrowseComp-Plus | 65.9% | Not measured | Only o3 measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index17 boards measured
| Benchmark | o3 | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| GPQA Diamond | 84.1% | Not measured | Only o3 measured |
| MMMU Pro (Vals AI) | 80.4% | Not measured | Only o3 measured |
| GPQA Diamond (Artificial Analysis run) | 82.7% | Not measured | Only o3 measured |
| Humanity's Last Exam (Artificial Analysis run) | 20.1% | Not measured | Only o3 measured |
| GPQA Diamond (Epoch AI run) | 81.8% | Not measured | Only o3 measured |
| ARC-AGI | 60.8% | Not measured | Only o3 measured |
| ARC-AGI-2 | 6.5% | Not measured | Only o3 measured |
| SimpleBench | 53.1% | Not measured | Only o3 measured |
| Chess puzzles | 37.0% | Not measured | Only o3 measured |
| Mystery game puzzles | 29.0% | Not measured | Only o3 measured |
| VPCT | 52.0% | Not measured | Only o3 measured |
| LMArena Text: hard prompts | 1402 | Not measured | Only o3 measured |
| LMArena Text: expert | 1402 | Not measured | Only o3 measured |
| LMArena Text: hard prompts in English | 1411 | Not measured | Only o3 measured |
| LMArena Vision: diagrams | 1220 | Not measured | Only o3 measured |
| LMArena Vision: homework | 1234 | Not measured | Only o3 measured |
| Kagi LLM Benchmark | 67.6% | Not measured | Only o3 measured |
| Neither model has a result on the other 6 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index11 boards measured
| Benchmark | o3 | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| AIME | 85.3% | Not measured | Only o3 measured |
| MATH 500 (Vals AI) | 94.6% | Not measured | Only o3 measured |
| MGSM (Vals AI) | 91.8% | Not measured | Only o3 measured |
| AA Math Index | 88.3 | Not measured | Only o3 measured |
| AIME 2025 (Artificial Analysis run) | 88.3% | Not measured | Only o3 measured |
| OTIS Mock AIME | 84.4% | Not measured | Only o3 measured |
| FrontierMath, tiers 1 to 3 | 33.3% | Not measured | Only o3 measured |
| MATH level 5 | 97.8% | Not measured | Only o3 measured |
| LMArena Text: math | 1426 | Not measured | Only o3 measured |
| LMArena Text: mathematical work | 1423 | Not measured | Only o3 measured |
| MathArena | 14.2% | Not measured | Only o3 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index17 boards measured
| Benchmark | o3 | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| MMLU Pro | 85.6% | Not measured | Only o3 measured |
| LegalBench (Vals AI) | 83.8% | Not measured | Only o3 measured |
| CorpFin (Vals AI) | 59.7% | Not measured | Only o3 measured |
| TaxEval (Vals AI) | 74.6% | Not measured | Only o3 measured |
| MortgageTax (Vals AI) | 65.7% | Not measured | Only o3 measured |
| MedQA (Vals AI) | 96.1% | Not measured | Only o3 measured |
| MedCode (Vals AI) | 47.3% | Not measured | Only o3 measured |
| MMLU Pro (Artificial Analysis run) | 85.3% | Not measured | Only o3 measured |
| SimpleQA Verified | 49.4% | Not measured | Only o3 measured |
| GeoBench | 74.0% | Not measured | Only o3 measured |
| LMArena Text: science | 1429 | Not measured | Only o3 measured |
| LMArena Text: medicine and healthcare | 1448 | Not measured | Only o3 measured |
| LMArena Text: legal and government | 1428 | Not measured | Only o3 measured |
| LMArena Text: business and finance | 1393 | Not measured | Only o3 measured |
| FACTS Benchmark Suite | 44.4% | Not measured | Only o3 measured |
| PRBench Finance | 47.7% | Not measured | Only o3 measured |
| PRBench Legal | 48.6% | Not measured | Only o3 measured |
| Neither model has a result on the other 3 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | o3 | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| Design Arena: websites | 1036 | Not measured | Only o3 measured |
| Design Arena: UI components | 1014 | Not measured | Only o3 measured |
| Design Arena: game dev | 1034 | Not measured | Only o3 measured |
| Design Arena: data viz | 1200 | Not measured | Only o3 measured |
| Design Arena: all code categories | 1020 | Not measured | Only o3 measured |
| Neither model has a result on the other 4 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index35 boards measured
| Benchmark | o3 | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 41.8% | Not measured | Only o3 measured |
| MedScribe (Vals AI) | 76.7% | Not measured | Only o3 measured |
| IFBench | 71.4% | Not measured | Only o3 measured |
| Long context reasoning (AA-LCR) | 74.7% | Not measured | Only o3 measured |
| DTBench | 84.8% | Not measured | Only o3 measured |
| LMCA | 39.7% | Not measured | Only o3 measured |
| Fiction.LiveBench | 88.9% | Not measured | Only o3 measured |
| Creative writing (Lech Mazur) | 83.9% | Not measured | Only o3 measured |
| CL-bench | 17.8% | Not measured | Only o3 measured |
| LMArena Text | 1410 | Not measured | Only o3 measured |
| LMArena Text: instruction following | 1368 | Not measured | Only o3 measured |
| LMArena Text: creative writing | 1359 | Not measured | Only o3 measured |
| LMArena Vision | 1214 | Not measured | Only o3 measured |
| LMArena Text: English | 1417 | Not measured | Only o3 measured |
| LMArena Text: non-English | 1401 | Not measured | Only o3 measured |
| LMArena Text: Chinese | 1437 | Not measured | Only o3 measured |
| LMArena Text: German | 1420 | Not measured | Only o3 measured |
| LMArena Text: Japanese | 1403 | Not measured | Only o3 measured |
| LMArena Text: Korean | 1370 | Not measured | Only o3 measured |
| LMArena Text: French | 1430 | Not measured | Only o3 measured |
| LMArena Text: Spanish | 1395 | Not measured | Only o3 measured |
| LMArena Text: Russian | 1406 | Not measured | Only o3 measured |
| LMArena Text: Polish | 1438 | Not measured | Only o3 measured |
| LMArena Text: multi-turn | 1405 | Not measured | Only o3 measured |
| LMArena Text: longer queries | 1372 | Not measured | Only o3 measured |
| LMArena Text: writing and language | 1372 | Not measured | Only o3 measured |
| LMArena Text: entertainment and media | 1373 | Not measured | Only o3 measured |
| LMArena Vision: English | 1221 | Not measured | Only o3 measured |
| LMArena Vision: Chinese | 1237 | Not measured | Only o3 measured |
| LMArena Vision: reading text | 1218 | Not measured | Only o3 measured |
| LMArena Vision: humor | 1222 | Not measured | Only o3 measured |
| LMArena Vision: captioning | 1210 | Not measured | Only o3 measured |
| LMArena Vision: recognizing things | 1234 | Not measured | Only o3 measured |
| LMArena Vision: creative writing | 1201 | Not measured | Only o3 measured |
| MultiChallenge | 56.6% | Not measured | Only o3 measured |
| Neither model has a result on the other 13 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 8B Lunaris costs less
Repository review
50K input + 3K output tokens
Llama 3 8B Lunaris costs less
Agent loop
200K input + 10K output tokens
Llama 3 8B Lunaris 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 | OpenAI o3 | Sao10K Llama 3 8B Lunaris |
|---|---|---|
| Maker | OpenAI | Sao10K |
| Weights | No public weights listed | Open weights |
| Released | April 16, 2025 | August 13, 2024 |
| Context window | 200K | 8K |
| Input $/Mtok | $2.00 | $0.04 |
| Output $/Mtok | $8.00 | $0.05 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | $0.571 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is o3 better than Llama 3 8B Lunaris for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick o3 for a larger context window (200K against 8K tokens).
Which is cheaper, o3 or Llama 3 8B Lunaris?
o3 costs $2.00 per million input tokens and $8.00 per million output tokens; Llama 3 8B Lunaris costs $0.04 and $0.05. Cost per solved task is known for o3 only.
Which has the bigger context window, o3 or Llama 3 8B Lunaris?
o3, with 200K tokens against 8K.
Has any benchmark tested both o3 and Llama 3 8B Lunaris?
No benchmark has tested both yet. o3 has results on Aider polyglot, SWE-bench Verified and SWE-bench Multimodal; Llama 3 8B Lunaris has none yet. Compare them on price and context instead. Data as of October 22, 2026.