Llama Guard 4 12B vs Pareto 26.10
Llama Guard 4 12B costs 17.8x less per output token than Pareto 26.10 ($0.18 vs $3.20 per million). Updated October 23, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.18
- Coding
- No data
- Overall
- No data
- Output $/M
- $3.20
Llama Guard 4 12B or Pareto 26.10: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Llama Guard 4 12B for output tokens 17.8x cheaper ($0.18 vs $3.20 per million).
No benchmark has tested either model yet, so price and context are the only way to compare them.
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
Long documents
Listed context window
Pareto 26.10
Pareto 26.10 takes 1.05M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama Guard 4 12B
Llama Guard 4 12B $0.0003, Pareto 26.10 $0.0024 per turn.
List prices
At a glance
- Coding index
- Llama Guard 4 12B not benchmarked, Pareto 26.10 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
- Llama Guard 4 12B $0.18 against Pareto 26.10 $3.20 per million output tokens, 17.8x apart.
- Context window
- Llama Guard 4 12B takes 164K tokens, Pareto 26.10 1.05M.
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.
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 Guard 4 12B costs less
Repository review
50K input + 3K output tokens
Llama Guard 4 12B costs less
Agent loop
200K input + 10K output tokens
Llama Guard 4 12B 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 Guard 4 12B | Pareto 26.10 |
|---|---|---|
| Maker | Meta Llama | Unbiased |
| Weights | Open weights | No public weights listed |
| Released | April 30, 2025 | October 15, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.18 | $0.80 |
| Output $/Mtok | $0.18 | $3.20 |
| 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 Llama Guard 4 12B better than Pareto 26.10 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Llama Guard 4 12B for output tokens 17.8x cheaper ($0.18 vs $3.20 per million).
Which is cheaper, Llama Guard 4 12B or Pareto 26.10?
Llama Guard 4 12B costs $0.18 per million input tokens and $0.18 per million output tokens; Pareto 26.10 costs $0.80 and $3.20. Cost per solved task is known for neither of them.
Which has the bigger context window, Llama Guard 4 12B or Pareto 26.10?
Pareto 26.10, with 1.05M tokens against 164K.
Has any benchmark tested both Llama Guard 4 12B and Pareto 26.10?
No benchmark has tested either model yet, so price and context are the only way to compare them. Data as of October 23, 2026.