Price Per TokenPrice Per Token
Meta-llama

Llama 3.1 405B (base) API Pricing 2026

Compare pricing, benchmarks, and providers for Llama 3.1 405B (base). Find the best value for your use case.

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Last updated: February 7, 2026 at 08:06 AM

Overview

Llama 3.1 405B (base) was released on August 2, 2024. Pricing starts at $4.00 per million input tokens and $4.00 per million output tokens. The model supports a context window of up to 33K tokens. API access is available through Meta-llama.

Context Window
33K
tokens
Pricing
Input$4.00
Output$4.00
per 1M tokens
Speed
Output-
TTFT-
median latency
Capabilities
Tools

Pricing Comparison

Compare Llama 3.1 405B (base) with 10 similar models by price.

Current Pricing (per 1M tokens)

11 models

Provider
Model
Input $/M
Output $/M
Coding
MMLU
GPQA
Context
Actions
$4.000
$4.000
32,768
$3.000
$15.000
59.0
86.0
72.7
1,000,000
$3.000
$15.000
81.9
86.6
87.7
256,000
$3.000
$15.000
42.5
79.9
69.3
131,072
$3.000
$15.000
44.9
83.7
68.3
1,000,000
$3.000
$15.000
27.5
75.5
57.8
200,000
$3.000
$15.000
39.4
80.3
65.6
200,000
$3.000
$3.000
16,000
$3.000
$5.000
16,384
$3.750
$7.500
6,144
$4.000
$8.000
131,072

* Some models use tiered pricing based on prompt length. Displayed prices are for prompts ≤ 200k tokens.

Compare Providers

Llama 3.1 405B (base) is available from multiple providers with different pricing and availability.

1
Providers
$4.000
Cheapest Input/M
$4.000
Cheapest Output/M
Hyperbolic
Best Price

Provider Pricing

1 models

Provider
Input $/M
Output $/M
Uptime
H
Hyperbolic
Best Price
$4.000
$4.000
-
Provider pricing data sourced from OpenRouter and Helicone

Cost vs. Quality

Compare Llama 3.1 405B (base)'s benchmark performance against all models.

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Frequently Asked Questions

Llama 3.1 405B (base) costs $0.004000 per 1,000 input tokens and $0.004000 per 1,000 output tokens.
Llama 3.1 405B (base) is available from 1 provider(s). Hyperbolic offers the best price.
We compare Llama 3.1 405B (base) with 10 similarly-priced models. See the benchmark scatter plot above to compare quality vs cost.

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