o3 Pro vs Llama 3 8B Lunaris
Llama 3 8B Lunaris costs 1600.0x less per output token than o3 Pro ($0.05 vs $80.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $80.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.05
o3 Pro 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 Pro for a larger context window (200K against 8K tokens).
No benchmark has tested both yet. o3 Pro has results on Aider polyglot, WeirdML and AA Intelligence Index; 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 Pro has a AA Intelligence Index result, 21.9.
Directional only
Long documents
Listed context window
o3 Pro
o3 Pro takes 200K tokens against 8K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3 8B Lunaris
o3 Pro $0.060, Llama 3 8B Lunaris $0.0001 per turn.
List prices
At a glance
- Coding index
- o3 Pro 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 Pro $80.00 against Llama 3 8B Lunaris $0.05 per million output tokens, 1600.0x apart.
- Context window
- o3 Pro 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 Index2 boards measured
| Benchmark | o3 Pro | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| Aider polyglot | 84.9% | Not measured | Only o3 Pro measured |
| WeirdML | 58.2% | Not measured | Only o3 Pro measured |
| Neither model has a result on the other 41 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | o3 Pro | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| AA Intelligence Index | 21.9 | Not measured | Only o3 Pro measured |
| Epoch Capabilities Index | 147.3 | Not measured | Only o3 Pro measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | o3 Pro | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| MCP Atlas | 44.5% | Not measured | Only o3 Pro measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | o3 Pro | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.5% | Not measured | Only o3 Pro measured |
| ARC-AGI | 59.3% | Not measured | Only o3 Pro measured |
| ARC-AGI-2 | 4.9% | Not measured | Only o3 Pro measured |
| Kagi LLM Benchmark | 72.1% | Not measured | Only o3 Pro measured |
| Neither model has a result on the other 19 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | o3 Pro | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| PRBench Finance | 49.1% | Not measured | Only o3 Pro measured |
| PRBench Legal | 49.7% | Not measured | Only o3 Pro measured |
| Neither model has a result on the other 18 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | o3 Pro | Llama 3 8B Lunaris | Leader |
|---|---|---|---|
| DTBench | 86.9% | Not measured | Only o3 Pro measured |
| LMCA | 38.5% | Not measured | Only o3 Pro measured |
| Fiction.LiveBench | 97.2% | Not measured | Only o3 Pro measured |
| Creative writing (Lech Mazur) | 84.4% | Not measured | Only o3 Pro measured |
| MultiChallenge | 62.4% | Not measured | Only o3 Pro measured |
| Neither model has a result on the other 43 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 Pro | Sao10K Llama 3 8B Lunaris |
|---|---|---|
| Maker | OpenAI | Sao10K |
| Weights | No public weights listed | Open weights |
| Released | June 10, 2025 | August 13, 2024 |
| Context window | 200K | 8K |
| Input $/Mtok | $20.00 | $0.04 |
| Output $/Mtok | $80.00 | $0.05 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is o3 Pro 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 Pro for a larger context window (200K against 8K tokens).
Which is cheaper, o3 Pro or Llama 3 8B Lunaris?
o3 Pro costs $20.00 per million input tokens and $80.00 per million output tokens; Llama 3 8B Lunaris costs $0.04 and $0.05. Cost per solved task is known for neither of them.
Which has the bigger context window, o3 Pro or Llama 3 8B Lunaris?
o3 Pro, with 200K tokens against 8K.
Has any benchmark tested both o3 Pro and Llama 3 8B Lunaris?
No benchmark has tested both yet. o3 Pro has results on Aider polyglot, WeirdML and AA Intelligence Index; Llama 3 8B Lunaris has none yet. Compare them on price and context instead. Data as of October 22, 2026.