Meta: Llama 3.1 8B Instruct API Pricing
Meta: Llama 3.1 8B Instruct costs $0.050 per 1M input tokens and $0.080 per 1M output tokens (cache reads: $0.025). Context window: 131K. Prices verified 2026-10-21 · source
Alternatives to consider
45% cheaper with nearly identical quality (20.1 vs 6.9)
+6.1 quality points for 20% more
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Token economics
| Token type | Price | vs base input |
|---|---|---|
| Standard input | $0.050 | — |
| Cache read | $0.025 | −50% |
| Output | $0.080 | — |
Prompt caching stores repeated context server-side: reads cost far less, but writes carry a one-time premium.
Training data ends here — newer events require retrieval or web search.
What would Meta: Llama 3.1 8B Instruct cost you per month?
| Workload | Requests/mo | Avg tokens (in/out) | Est. monthly cost |
|---|---|---|---|
| Light chatbot | 10,000 | 800 / 400 | $0.72 |
| Coding agent | 5,000 | 8,000 / 2,000 | $2.80 |
| RAG pipeline | 30,000 | 4,000 / 500 | $7.20 |
| Doc summarizer | 2,000 | 20,000 / 1,000 | $2.16 |
Estimates use list prices without prompt caching. Caching can cut input cost by up to 90% on repeated context.
About Meta: Llama 3.1 8B Instruct
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to...
Compare Meta: Llama 3.1 8B Instruct with
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Popular head-to-heads — see all on the comparisons index.
Frequently asked questions
How much does Meta: Llama 3.1 8B Instruct cost?
Meta: Llama 3.1 8B Instruct costs $0.050 per 1M input tokens and $0.080 per 1M output tokens; cached input tokens cost $0.025 per 1M. Verified 2026-10-21 — provider source.
What is the context window?
131K tokens, with up to 118K output tokens per response. That's roughly 164 pages of text in a single request.
Does it support prompt caching?
Yes — cached input is $0.025/1M, about 50% cheaper than standard input. Agents and RAG workloads with repeated context benefit most.
What's a cheaper alternative?
Mistral: Mistral Nemo saves about 50% on a typical workload with comparable quality.
Official resources
- Meta: Llama 3.1 8B Instruct on OpenRouter — live endpoint, pricing source of record.
- Artificial Analysis leaderboard → — independent intelligence and performance rankings.
- Llama models → — first-party model and license information.
- LMArena leaderboard → — independent human-preference rankings.
- Shred your current bill — paste a CSV and see if switching saves money.