Best cost/speed trade-off
parasail/fp8$0.3133 / 1M tokens
9.46 s estimated response
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meta-llama/llama-3.3-70b-instruct
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
At a glance
Based on 1,000 input and 500 output tokens using the latest published median speed data.
Visual comparison
Compare published endpoint pricing and estimated response time visually.
USD per 1 million tokens for input and output. Lower is better.
DeepInfra has the lowest estimated cost for 1,000 input and 500 output tokens at $0.00026.
Based on 1,000 input and 500 output tokens. Cost is shown in USD per 1 million tokens. Lower and further left is better; the single best cost/speed trade-off appears at full opacity.
12 providers have complete pricing and speed data. Parasail is closest to the ideal combination of lowest cost and fastest response.
Server-rendered comparison
Prompt and completion prices are effective USD per token as published by OpenRouter. Missing speed data never removes an endpoint.
| Provider / route | Current pricing ↗ | Speed measurements | Endpoint details |
|---|---|---|---|
| Provider / route | Current pricing
| Speed measurements
| Endpoint details
14 parametersfrequency_penalty, logit_bias, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, temperature, tool_choice, tools, top_k, top_p |
| Provider / route Nebius nebius/fp8 | Current pricing
| Speed measurements
| Endpoint details
14 parametersfrequency_penalty, logit_bias, max_tokens, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_p |
| Provider / route AkashML akashml/fp8 | Current pricing
| Speed measurements
| Endpoint details
15 parametersfrequency_penalty, logprobs, max_tokens, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p |
| Provider / route NovitaAI novita/bf16 | Current pricing
| Speed measurements
| Endpoint details
14 parametersfrequency_penalty, logprobs, max_tokens, presence_penalty, repetition_penalty, response_format, seed, stop, temperature, tool_choice, tools, top_k, top_logprobs, top_p |
| Provider / route | Current pricing
| Speed measurements
| Endpoint details
14 parametersfrequency_penalty, logit_bias, logprobs, max_tokens, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_logprobs, top_p |
| Provider / route Cloudflare cloudflare/fp8 | Current pricing
| Speed measurements
| Endpoint details
14 parametersfrequency_penalty, logit_bias, logprobs, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, temperature, top_k, top_logprobs, top_p |
| Provider / route | Current pricing
| Speed measurements
| Endpoint details
5 parametersmax_tokens, stop, temperature, top_k, top_p |
| Provider / route Groq groq | Current pricing
| Speed measurements
| Endpoint details
8 parametersmax_tokens, response_format, seed, stop, temperature, tool_choice, tools, top_p |
| Provider / route Weights & Biases wandb/fp16 | Current pricing
| Speed measurements
| Endpoint details
15 parametersfrequency_penalty, logprobs, max_tokens, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p |
| Provider / route Google Vertex google-vertex | Current pricing
| Speed measurements
| Endpoint details
5 parametersmax_tokens, response_format, seed, temperature, top_p |
| Provider / route Google Vertex google-vertex/us-central1 | Current pricing
| Speed measurements
| Endpoint details
12 parametersfrequency_penalty, max_tokens, presence_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_p |
| Provider / route Together together/fp8 | Current pricing
| Speed measurements
| Endpoint details
14 parametersfrequency_penalty, logit_bias, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_p |
Endpoint data fetched .
Llama 3.3 70B Instruct deployment guide
Llama 3.3 70B Instruct is indexed here as a text model by Meta, with 12 provider endpoints from DeepInfra, Nebius, AkashML, NovitaAI, Parasail, and others. The comparison preserves each exact OpenRouter routing tag so pricing and performance observations can be connected to the route an application would actually request.
The model publishes a 131.1K-token context window. It accepts text input and returns text output. 17 distinct supported parameters appear across the listed routes. Confirm limits on the specific endpoint rather than assuming every host exposes the same configuration.
DeepInfra currently has the lowest estimated cost for the standard 1,000-input/500-output-token sample at $0.00026. Input-heavy and output-heavy applications can produce a different result, so review both per-million-token prices in the endpoint table.
SambaNova currently has the shortest estimated 500-token response at 6.45 seconds. Parasail is the single endpoint closest to the current ideal cost/speed combination. Recent observations can change, so validate finalists with your own prompts.