Where is the Llama 3.3 70B Instruct documentation?

The Llama 3.3 70B Instruct documentation on OpenRouter includes the Price Drops and Llama 3.3 70b blog post. The quickstart covers API keys and your first request, and the API reference lists every parameter.

How much does Llama 3.3 70B Instruct cost?

Llama 3.3 70B Instruct costs $0.10/M input tokens and $0.32/M output tokens.

What is the context length of Llama 3.3 70B Instruct?

Llama 3.3 70B Instruct has a 131,072 token context window. It supports up to 16,384 completion tokens.

Does Llama 3.3 70B Instruct support tool calling and structured outputs?

Yes. Llama 3.3 70B Instruct accepts tools and tool_choice for function calling on 5 of the 8 providers serving it, and requests that send tools are routed to those providers. It also supports structured outputs via a JSON schema in response_format.

Which providers serve Llama 3.3 70B Instruct?

Llama 3.3 70B Instruct is served by 8 providers on OpenRouter: DeepInfra (Turbo), AkashML, Parasail, Cloudflare, Groq, SambaNova Turbo, CoreWeave, and Google Vertex. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.

When was Llama 3.3 70B Instruct released?

Llama 3.3 70B Instruct was released on December 6, 2024. Its knowledge cutoff is December 31, 2023.

Meta: Llama 3.3 70B Instruct

meta-llama/llama-3.3-70b-instruct

Model weights

Compare

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 is optimized for multilingual dialogue use cases and outperforms many of the available open source and closed chat models on common industry benchmarks.

Supported languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.

Model Card

Modalities

In / out price

$0.10 / $0.32per 1M

Context

131K

Released

Dec 6, 2024

Knowledge cutoff

Dec 2023

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Latency / throughput


	$0.71	$0.71	$0.71	0.13s	86 tok/s	100.00%
	$0.60	$1.20	--	0.64s	125 tok/s	99.54%
	$0.293	$2.253	--	1.21s	49 tok/s	97.90%
	$0.22	$0.50	$0.11	0.93s	39 tok/s	99.52%
BYOK only	$0.72	$0.72	--	--	--	--
BYOK only	$0.72	$0.72	--	--	--	--
	$0.59	$0.79	$0.295	0.45s	232 tok/s	99.97%
	$0.20	$0.52	$0.10	0.75s	37 tok/s	98.75%
	$0.10	$0.32	--	0.51s	26 tok/s	99.47%

Input $0.71Output $0.71
86 tok/s100.00% uptime
Input $0.60Output $1.20
125 tok/s99.54% uptime
Input $0.293Output $2.253
49 tok/s97.90% uptime
Input $0.22Output $0.50
39 tok/s99.52% uptime
Input $0.72Output $0.72
BYOK only
-- tok/s-- uptime
Input $0.72Output $0.72
BYOK only
-- tok/s-- uptime
Input $0.59Output $0.79
232 tok/s99.97% uptime
Input $0.20Output $0.52
37 tok/s98.75% uptime
Input $0.10Output $0.32
26 tok/s99.47% uptime

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input

$0.4432/M tokens

Output

$0.6912/M tokens

Llama 3.3 70B Instruct — Price history

Price history

No effective price data for this selection

$0.0998	$0.314	0.0%	9.6%
$0.1603	$0.517	39.5%	19.4%
$0.1911	$0.498	26.0%	10.3%
$0.2928	$2.249	0.0%	2.4%
$0.5897	$0.786	0.0%	26.0%
$0.5996	$1.196	0.0%	4.9%
$0.7097	$0.706	53.7%	27.5%
—	—	—	—
—	—	—	—

Effective in $0.0998Effective out $0.314
Token share
9.6%
Effective in $0.1603Effective out $0.517
Token share
19.4%
Effective in $0.1911Effective out $0.498
Token share
10.3%
Effective in $0.2928Effective out $2.249
Token share
2.4%
Effective in $0.5897Effective out $0.786
Token share
26.0%
Effective in $0.5996Effective out $1.196
Token share
4.9%
Effective in $0.7097Effective out $0.706
Token share
27.5%
Effective in —Effective out —
Token share —
Effective in —Effective out —
Token share —

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Throughput

232tok/s

P50, best across providers

Latency

0.13s

P50, best provider

Latency / throughput

AutoExacto benchmarks

GPQA DiamondTAU-BenchCloudflare50.0%--Groq49.9%--Parasail47.9%--Novita47.4%--SambaNova Turbo47.4%--

+5 more providers

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)

99.99%

Availability (3d)

99.94%

Availability over the last 3 days

Last 72 hours

Availability 99.94%

3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability

99.96%

Without Routing

97.17%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for Meta: Llama 3.3 70B Instruct (Artificial Analysis)
Source	Benchmark	Score
Artificial Analysis	Llama 3.3 Instruct 70B Coding Index	11.9
Artificial Analysis	Llama 3.3 Instruct 70B GPQA Diamond	49.8%
Artificial Analysis	Llama 3.3 Instruct 70B HLE	3.6%
Artificial Analysis	Llama 3.3 Instruct 70B IFBench	47.1%
Artificial Analysis	Llama 3.3 Instruct 70B τ²-Bench Telecom	26.6%
Artificial Analysis	Llama 3.3 Instruct 70B AA-LCR	15.7%
Artificial Analysis	Llama 3.3 Instruct 70B GDPval-AA	0.0%
Artificial Analysis	Llama 3.3 Instruct 70B CritPt	0.0%
Artificial Analysis	Llama 3.3 Instruct 70B LiveCodeBench	28.8%
Artificial Analysis	Llama 3.3 Instruct 70B Terminal-Bench Hard	3.0%
Artificial Analysis	Llama 3.3 Instruct 70B Terminal-Bench 2.1	4.9%
Artificial Analysis	Llama 3.3 Instruct 70B MMLU-Pro	71.3%
Artificial Analysis	Llama 3.3 Instruct 70B AIME 2025	7.7%
Artificial Analysis	Llama 3.3 Instruct 70B AIME	30.0%
Artificial Analysis	Llama 3.3 Instruct 70B MATH-500	77.3%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

DIAL-590 offline benchmark

new

4.04Btokens

ESMED Email App V3

new

1.74Btokens

Router

new

1.07Btokens

JuicyChat

new

1Btokens

OpenClaw

OpenClaw is an open-source AI agent that connects to your messaging apps and takes real actions on your behalf, from running commands and browsing the web to managing files and sending emails.

928Mtokens

Rest of OpenRouter

835M

Top 5 Apps

18.5M

Not currently available through EU in-region routing. In-region routing docs

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Meta: Llama 3.3 70B Instruct

Providers