ModelPriceWatch.com
Last scan 2026-09-15 Models tracked 259 Providers 32 Cheapest paid Granite 4.0 H Micro $0.017/Mtok in Every price links to its source

Llama 3.3 70B

by Meta · 70B parameters

Current open weights open weights cheap tier

Today's price · per 1M tokens

Input

$0.590

per 1M tokens

Output

$0.790

per 1M tokens

Blended

$0.640

blended $/1M — 3:1 weighted input:output

Source: official Meta pricing · read MODELPRICEWATCH.COM · 2026-09-15

Price receipt

We read Meta's own pricing page on and found Llama 3.3 70B listed with a price on the same row — that read is where the number above comes from. We keep the page text we read; its content hash is 5268b840bd.

Available on 2 hosts

cheapest blended first · $ per 1M tokens

Llama 3.3 70B is sold by 2 providers. Prices are per 1M tokens (blended = (3×input + 1×output) ÷ 4). The first-party row is the model maker; “vs first-party” shows each host’s blended price relative to it.

Llama 3.3 70B price on every host still selling it, per 1M tokens, cheapest blended first
Host Input Output Blended vs first-party
Meta first-party $0.590 $0.790 $0.640
Together details → $1.04 $1.04 $1.04 +63%
Each host links to its provider page and official pricing. Prices refresh twice daily. MODELPRICEWATCH.COM · 2026-09-15

Overview

Widely used open-weights model. Cheapest hosted price via Groq: $0.59/$0.79 per 1M tokens (also on Together at $1.04/$1.04).

Run it yourself

Deploy this open model on rented GPUs

Open weights mean you can self-host instead of paying per-token API prices. These platforms let you serve it on demand — often cheaper at scale.

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Capabilities

struck through = not supported
Input 1/5
Text Image Audio Video PDF
Output 1/5
Text Image Audio Video Embedding
Features 2/9
Prompt caching Reasoning Coding Fast inference Long context Open weights Multimodal Web search Realtime

Benchmark performance

accuracy % · higher is better
Avg benchmark score46.6%
Perf per $/Mtok72.8
GPQA Diamond
50.5%
SWE-Bench Verified
22%
Humanity's Last Exam
10%
ARC-AGI 2
12%
AIME 2025
38%
MMMLU
72%
BFCL
77.3%
HumanEval
78%
MATH 500
60%
How it stacks up
  • Ranks #70 of 84 benchmarked models by average score
  • Ranks #142 of 181 comparably-measured models by percentile score, across 9 independent measurements
  • Ranks #86 of 181 comparably-tested models by normalized performance per dollar
  • Strongest at BFCL — 77.3%, #4 of 24

2500 tokens/sec output 0.52s latency to first token (TTFT)

Source: Vellum LLM Leaderboard · updated · See full rankings →

Specifications

Provider
Meta
Context window
128K tokens
Modality
text
Parameters
70B
Open source
Yes — open weights available
Released
Status
Current
Last updated
Tags
open-weights

Availability verified: listed on Meta's own page