gpt-5.6-luna
Input price$0.2
Output price$1.2
GroqText
llama-3.3-70b-versatile
llama-3.3-70b-versatile is Groq's model at $0.59 input and $0.79 output per million tokens, with a 128K context window. On a typical 3:1 input-to-output mix that blends to roughly $0.64 per million tokens, placing it in the mid-range band of the 89 models tracked here — cheaper than 60% of them.
Context window128K
Input price$0.59 / 1M
Output price$0.79 / 1M
Output speed300 tok/s
Quality score78
Data updatedUpdated Jun 2026
Price verified2026-07-10 · OpenRouter
By price, llama-3.3-70b-versatile ranks 40th cheapest of 89 on input and 25th on output. Its quality score of 78 ranks 69th of 89, and on value (quality score ÷ output price) it ranks 23rd of 89. Its blended rate sits 79% below the catalog average.
In real billing terms: a support chatbot handling 50,000 turns a month (2,000 input / 500 output tokens each) costs about $79 per month on llama-3.3-70b-versatile, while a RAG workload of 20,000 queries (8,000 input / 800 output tokens each) runs about $107. Because output is priced 1.3× input here, long-generation tasks scale cost fastest — cap output length before you optimise anything else.
A 128K context window holds roughly 171 pages of A4 text (at ~750 tokens per page), ranking 74th of 89 here. That covers typical RAG and multi-turn chat, though book-length inputs still need retrieval and chunking. Output runs at about 300 tok/s (3rd fastest of 89), fast enough for real-time interaction and high-throughput batches.
We track 1 Groq models, and llama-3.3-70b-versatile's blended rate sits 0% above that provider's average. If your task tolerates a little less headroom, qwen3.7-flash (Alibaba) blends about 91% cheaper at a quality score of 82, and is worth benchmarking first. Going the other way, mercury-2.5-preview scores 82 on quality for about 89% less.
Estimated monthly cost
Monthly API spend across four common workloads, next to the cheapest model we track.
| Workload | Usage assumption | This model | Cheapest model |
|---|---|---|---|
| Support chatbot | 2,000 input / 500 output tokens per turn, 50,000 turns per month | $79 | $3.00 |
| RAG document Q&A | 8,000 input / 800 output tokens per query, 20,000 queries per month | $107 | $3.84 |
| Coding assistant | 12,000 input / 2,000 output tokens per request, 10,000 requests per month | $87 | $3.20 |
| Batch summarization | 4,000 input / 400 output tokens per item, 200,000 items per month | $535 | $19 |
Derived directly from the rates on this page. Excludes prompt caching, batch discounts and free tiers.
How it compares
The alternatives worth benchmarking alongside it, from the same dataset.
| Model | Provider | Blended /1M | Quality | Price delta |
|---|---|---|---|---|
| llama-3.3-70b-versatile | Groq | $0.64 | 78 | — |
| qwen3.7-flashCheaper option | Alibaba | $0.055 | 82 | -91% |
| mercury-2.5-previewHigher quality | Inception | $0.068 | 82 | -89% |
| Phi-4-miniBest value overall | Microsoft | $0.025 | 68 | -96% |
Best for
ChatbotAffordableFast
Modalities
Text
Where it fits — and where it doesn't
Good fit
- Chat and support: natural multi-turn conversation for user-facing products.
- High throughput and real-time UX: 300 tok/s keeps streamed responses feeling instant.
Poor fit
- Hard reasoning: a quality score of 78 is on the low side here; pick a stronger model for complex planning or maths.
- Image understanding: this model is text-only, so vision tasks need a multimodal alternative.
Frequently asked questions
How much does the llama-3.3-70b-versatile API cost?
llama-3.3-70b-versatile costs $0.59 per million input tokens and $0.79 per million output tokens. On a 3:1 input-to-output mix that blends to about $0.64 per million tokens.
What does llama-3.3-70b-versatile cost per month?
It depends on volume. Using the four worked scenarios on this page: a support chatbot runs about $79/month, RAG document Q&A about $107/month, a coding assistant about $87/month, and batch summarization about $535/month. Plug your own token counts into the cost calculator for a tailored figure.
How large is the llama-3.3-70b-versatile context window?
128K tokens — roughly 171 pages of A4 text at ~750 tokens per page, ranking 74th of the 89 models tracked here.
llama-3.3-70b-versatile or qwen3.7-flash — which is better value?
qwen3.7-flash blends to about $0.055 per million tokens versus $0.64 for llama-3.3-70b-versatile — roughly 91% cheaper — at a quality score of 82 against 78. If that quality gap does not show up on your task, take the cheaper one; if it does, stay with llama-3.3-70b-versatile. Benchmark both on your own data before deciding.
What is llama-3.3-70b-versatile best suited for?
Tagged use cases: chatbot, cheap, fast. Chat and support: natural multi-turn conversation for user-facing products. Less suitable: Hard reasoning: a quality score of 78 is on the low side here; pick a stronger model for complex planning or maths.
How current is this llama-3.3-70b-versatile pricing?
Pricing here was last verified on 2026-07-10 against OpenRouter. llmprice.app runs a daily collection job, but providers can change rates between runs — confirm against Groq's official pricing page before you commit.
Estimate the real cost of this model
Bring tokens per request and monthly volume into the calculator to compare total model costs.
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Pricing, speed and quality scores change over time. Confirm official documentation before production use.