Is Llama 3.2 1B Instruct a good deal?
Whether anything in this catalogue beats Llama 3.2 1B Instruct on both quality and price, and what you give up if it does. A computation on the current catalogue, not an opinion.
13 undominated of 136 · Sep 23, 2026
As of Sep 23, 2026, Llama 3.2 1B Instruct is dominated for Balanced on LMArena. Llama 3.1 8B Instruct scores 132.0 higher and costs 18% less, with a covering envelope. 13 of 136 rated, priced standard models are undominated.
Inspect model evidence Compare differences & requirements
Llama 3.1 8B Instruct is both better and cheaper than Llama 3.2 1B Instruct: 132.0 points higher on LMArena and 18% less per million tokens, $0.01 cheaper at this mix.
LMArena Elo · higher is better
Scale starts at 1040 Elo
1054.5
Effective $/M · Balanced · lower is better
$0.071/M
LMArena Elo · higher is better
Scale starts at 1040 Elo
1186.5
Effective $/M · Balanced · lower is better
$0.058/M
Llama 3.2 1B Instruct takes text, returns up to 54,000 tokens from a 60,000-token context, and is listed by 1 seller.
Compared against 136 rated, priced models on this lens: 1 model dominates it and gives up nothing, 3 more dominate it but give something up. Llama 3.2 1B Instruct scores 1054.5 at $0.07 per million tokens for this mix.
Envelope-safe replacements
Each row scores at least as high, costs no more, and covers this model’s context, output, modalities, tools, and reasoning. A cheaper narrower model is not listed here.
| Model | LMArena | Effective $/M | You save |
|---|---|---|---|
| Llama 3.1 8B Instruct | 1186.5 +132.0 | $0.058/M | 18% |
Higher score, lower price, named losses
Not a drop-in. The loss is why these are not a recommendation.
| Model | LMArena | Effective $/M | You give up |
|---|---|---|---|
| Gemma 3 4B | 1290.7 | $0.063/M | max output |
| gpt-oss-20b | 1287.3 | $0.036/M | max output |
| Mistral Small 3 | 1233.5 | $0.058/M | context, max output |
The link keeps the model and mix, using the current catalogue. Monthly spend and switching cost stay in this browser tab and are left out of the link.
Saved decision references
Save the model, workload, catalogue date and capability-preservation rule in this browser. Spend, switching cost and bill contents are not saved. No account or notifications.
Constraint: replacements must preserve the model’s capabilities; any losses remain named trade-offs.
Historical decisions cannot be fully replayed from saved references: past prices, scores and capability evidence are not stored.