Llama 3.1 70B Instruct API Pricing
Meta · context window 131K · prices updated 2026-09-15
Where Llama 3.1 70B Instruct sits on price
At $0.4 per million output tokens, Llama 3.1 70B Instruct is a budget tier model — 5.2× cheaper than the median output price of $2.08, which puts it cheaper than 84% and pricier than 16% of the models we track. It sits 7th cheapest of the 8 Meta models we track. Output is only 1.0× the input price, an unusually flat spread: long prompts hurt about as much as long answers, so prompt size is where the savings are.
What real workloads cost on Llama 3.1 70B Instruct
These three workloads are the ones teams actually run on a budget-priced model — a $0.4/1M model is not bought for the same job as one ten times the price.
| Workload | Per request | Per month |
|---|---|---|
| High-volume classification — 200K requests/day (400 in / 20 out) Short output, huge volume: the input price dominates the bill. | $0.0002 | $1008 |
| Small app — 1K requests/day (500 in / 150 out) The baseline most side projects actually run at. | $0.0003 | $7.80 |
| Document pipeline — 10K docs/day (3K in / 500 out) Batch-friendly: no user waiting, so a ~50% batch discount usually applies. | $0.0014 | $420 |
Model your exact traffic in the API cost calculator — it preloads Llama 3.1 70B Instruct with caching and batch options.
Llama 3.1 70B Instruct price history
Meta last cut Llama 3.1 70B Instruct's output price on Sep 13, 2026 (-44% per output token), from $0.72/$0.72 to $0.4/$0.4 per 1M in/out. That is one of 2 repricings in the 44 days we have tracked it — worth knowing before you hard-code today's rate into a budget.
| Date | Input /1M | Output /1M | Output change |
|---|---|---|---|
| Aug 2, 2026 (tracking began) | $0.4 | $0.4 | — |
| Sep 12, 2026 | $0.72 | $0.72 | +80% |
| Sep 13, 2026 | $0.4 | $0.4 | -44% |
Change-points from our daily price snapshots (tracking since Aug 2, 2026; intraday moves between snapshots are not captured).
Llama 3.1 70B Instruct vs Qwen2.5 72B Instruct
The closest-priced alternative from another vendor is Qwen2.5 72B Instruct (Alibaba (Qwen)) — priced within a rounding error on output, with $0.04 less per million input tokens. When two models land this close on price, the decision is quality on your own workload, not the price sheet: run 50 real requests through both and compare.
See Qwen2.5 72B Instruct pricing →Cheaper alternatives
More Meta models
Frequently asked questions
› How much does the Llama 3.1 70B Instruct API cost?
Llama 3.1 70B Instruct costs $0.4 per million input tokens and $0.4 per million output tokens and no discounted cached-input tier. That works out to roughly 2,500,000 output tokens per dollar.
› What does the high-volume classification workload cost on Llama 3.1 70B Instruct?
High-volume classification — 200K requests/day (400 in / 20 out) costs about $0.0002 per request and $1008 per month on Llama 3.1 70B Instruct. Short output, huge volume: the input price dominates the bill.
› What does it cost to fill Llama 3.1 70B Instruct's 131K context window?
Sending 131K of input in a single request costs $0.0524 at $0.4 per million tokens — before any output. There is no cached-input tier on this model, so every repeat of that context is billed at full price. This is why large context windows are cheap to advertise and expensive to actually use.
› Is Llama 3.1 70B Instruct worth the price?
Llama 3.1 70B Instruct is in the cheapest end of the market — cheaper than 84% of the models we track. At this price the question is not cost but capability: it is a good fit for classification, extraction, routing and bulk summarisation, and a poor fit for multi-step reasoning where a wrong answer costs more than the tokens saved.