Claude Fable 5$22.000/MClaude Opus 4.8$11.000/MClaude Opus 4.7$11.000/MClaude Opus 4.6$11.000/MClaude Opus 4.5$33.000/MClaude Sonnet 3.7$6.600/MClaude Opus 3$33.000/MClaude 2.1$12.800/MClaude 2$12.800/MGPT-5.5$12.500/MGPT-5.2$5.425/MGPT-5.2-Codex$5.425/MGPT-5$3.875/MGPT-4.5$97.500/MGPT-4 Turbo Preview$16.000/MGPT-4$39.000/MGPT-4-32k$78.000/Mo3$19.000/Mo3-mini$2.090/Mo4-mini$2.090/Mo1$28.500/Mo1-mini$5.700/Mo1-preview$28.500/MGemini 3.5 Pro$5.000/MGemini 3.1 Pro$5.000/MGemini 3 Pro$5.000/MGemini 2.5 Pro$3.875/MGemini 1.5 Pro$2.375/MGemini 1.0 Ultra$12.000/MGemini 1.0 Pro$0.800/MClaude Fable 5$22.000/MClaude Opus 4.8$11.000/MClaude Opus 4.7$11.000/MClaude Opus 4.6$11.000/MClaude Opus 4.5$33.000/MClaude Sonnet 3.7$6.600/MClaude Opus 3$33.000/MClaude 2.1$12.800/MClaude 2$12.800/MGPT-5.5$12.500/MGPT-5.2$5.425/MGPT-5.2-Codex$5.425/MGPT-5$3.875/MGPT-4.5$97.500/MGPT-4 Turbo Preview$16.000/MGPT-4$39.000/MGPT-4-32k$78.000/Mo3$19.000/Mo3-mini$2.090/Mo4-mini$2.090/Mo1$28.500/Mo1-mini$5.700/Mo1-preview$28.500/MGemini 3.5 Pro$5.000/MGemini 3.1 Pro$5.000/MGemini 3 Pro$5.000/MGemini 2.5 Pro$3.875/MGemini 1.5 Pro$2.375/MGemini 1.0 Ultra$12.000/MGemini 1.0 Pro$0.800/M
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MetaEfficient

Llama 3.3 70B

Open

The most-deployed open-weights chat model in 2025 — strong reasoning at 70B with broad inference-provider support.

Llama 3.3 70B is a efficient AI model from Meta. It costs $0.230 per million input tokens and $0.400 per million output tokens (blended $0.281/M), with a 128K-token context window.

Modalities textOfficial model page ↗API docs ↗Compare with another model →Estimate monthly cost →
INPUT
$0.230/M
per million input tokens
OUTPUT
$0.400/M
per million output tokens
BLENDED 70/30
$0.281/M
default reference rate · how it's calculated →
CONTEXT
128K
128,000 tokens
What it's good at
  • Strong open chat baseline
  • Cheap on Groq/Cerebras
  • 128K context
  • Wide ecosystem
Typical use cases
  • Self-hosted production chat
  • Cost benchmarking
  • RAG
Benchmarks
vs. best public score
MMLU86%
Multitask academic knowledge across 57 subjects.
GPQA Diamond50%
Graduate-level science questions, "Google-proof".
MATH77%
High-school competition math problems.
HumanEval80%
Python function synthesis from docstrings.
LMArena Elo1257 Elo
Crowd-sourced head-to-head preference Elo rating.
Hand-curated from each provider's published reports and public leaderboards. Methodology varies across sources — treat as directional rather than authoritative.
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Llama 4 Maverick
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in $0.200/Mout $0.600/M
Llama 4 Scout
Efficient · 512K ctx
in $0.100/Mout $0.350/M
Llama 3.1 405B
Large · 128K ctx
in $0.800/Mout $0.800/M
Llama 3.1 70B
Balanced · 128K ctx
in $0.350/Mout $0.400/M
Llama 3.1 8B
Compact · 128K ctx
in $0.100/Mout $0.100/M
Llama 3.2 90B Vision
Vision · 128K ctx
in $0.880/Mout $0.880/M
Frequently asked questions

How much does Llama 3.3 70B cost?

Llama 3.3 70B costs $0.230 per million input tokens and $0.400 per million output tokens, for a blended reference rate of $0.281 per million tokens.

What is Llama 3.3 70B's context window?

Llama 3.3 70B supports up to 128K tokens of context (128,000 tokens).

What is Llama 3.3 70B best for?

Llama 3.3 70B is well suited to Strong open chat baseline, Cheap on Groq/Cerebras and 128K context.

Who makes Llama 3.3 70B?

Llama 3.3 70B is developed and served by Meta.