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Hyperbolic: Models Quality, Performance & Price

Analysis of Hyperbolic's models across key metrics including quality, price, output speed, latency, context window & more. This analysis is intended to support you in choosing the best model provided by Hyperbolic for your use-case. For more details including relating to our methodology, see our FAQs. Models analyzed: Llama 3.3 70B, Llama 3.1 405B, Llama 3.1 70B, Llama 3.1 8B, Llama 3.2 3B, Pixtral 12B, DeepSeek R1, DeepSeek V3 (FP8), DeepSeek-V2.5, Qwen2.5 72B, Qwen2.5 Coder 32B, QwQ 32B-Preview, and Llama 3 70B.
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Hyperbolic Model Comparison Summary

Quality:Qwen2.5 72B logo Qwen2.5 72B and Llama 3.1 405B logo Llama 3.1 405B are the highest quality models offered by Hyperbolic, followed by Llama 3.3 70B logo Llama 3.3 70B, Qwen2.5 Coder 32B logo Qwen2.5 Coder 32B & Llama 3.1 70B logo Llama 3.1 70B.Output Speed (tokens/s):Llama 3.2 3B logo Llama 3.2 3B (201 t/s) and Llama 3.1 8B logo Llama 3.1 8B (115 t/s) are the fastest models offered by Hyperbolic, followed by Pixtral 12B logo Pixtral 12B, Qwen2.5 Coder 32B logo Qwen2.5 Coder 32B & QwQ 32B-Preview logo QwQ 32B-Preview.Latency (seconds):Llama 3.1 8B logo Llama 3.1 8B (0.41s) and  Llama 3.2 3B logo Llama 3.2 3B (0.43s) are the lowest latency models offered by Hyperbolic, followed by Pixtral 12B logo Pixtral 12B, Qwen2.5 Coder 32B logo Qwen2.5 Coder 32B & QwQ 32B-Preview logo QwQ 32B-Preview.Blended Price ($/M tokens):Pixtral 12B logo Pixtral 12B ($0.10) and Llama 3.1 8B logo Llama 3.1 8B ($0.10) are the cheapest models offered by Hyperbolic, followed by Llama 3.2 3B logo Llama 3.2 3B, Qwen2.5 Coder 32B logo Qwen2.5 Coder 32B & QwQ 32B-Preview logo QwQ 32B-Preview.Context Window Size:Qwen2.5 72B logo Qwen2.5 72B (131k) and Qwen2.5 Coder 32B logo Qwen2.5 Coder 32B (131k) are the largest context window models offered by Hyperbolic, followed by DeepSeek R1 logo DeepSeek R1, DeepSeek V3 (FP8) logo DeepSeek V3 (FP8) & Llama 3.3 70B logo Llama 3.3 70B.

Highlights

Quality
Artificial Analysis Quality Index; Higher is better
Speed
Output Tokens per Second; Higher is better
Price
USD per 1M Tokens; Lower is better
Parallel Queries:
Prompt Length:
Features
Model Quality
Price
Output tokens/s
Latency
Further
Analysis
Hyperbolic logo
Meta logo
Llama 3.3 70B
128k
74
$0.40
24.4
0.54
Hyperbolic logo
Meta logo
Llama 3.1 405B
128k
75
$4.00
7.7
0.83
Hyperbolic logo
Meta logo
Llama 3.1 70B
128k
69
$0.40
25.0
0.65
Hyperbolic logo
Meta logo
Llama 3.1 8B
128k
53
$0.10
115.2
0.41
Hyperbolic logo
Meta logo
Llama 3.2 3B
128k
48
$0.10
200.5
0.43
Hyperbolic logo
Mistral logo
Pixtral 12B
128k
57
$0.10
76.7
0.45
Hyperbolic logo
DeepSeek logo
DeepSeek R1
128k
89
$2.00
13.7
104.27
Hyperbolic (FP8) logo
DeepSeek logo
DeepSeek V3 (FP8)
128k
79
$0.25
5.5
1.56
Hyperbolic logo
DeepSeek logo
DeepSeek-V2.5
128k
$2.00
7.5
0.78
Hyperbolic logo
Alibaba logo
Qwen2.5 72B
131k
77
$0.40
27.7
0.58
Hyperbolic logo
Alibaba logo
Qwen2.5 Coder 32B
131k
72
$0.20
36.6
0.48
Hyperbolic logo
Alibaba logo
QwQ 32B-Preview
33k
$0.20
35.4
0.49
Hyperbolic logo
Meta logo
Llama 3 70B
8k
62
$0.40
32.8
0.60

Key definitions

Artificial Analysis Quality Index: Average result across our evaluations covering different dimensions of model intelligence. Currently includes MMLU, GPQA, Math & HumanEval. OpenAI o1 model figures are preliminary and are based on figures stated by OpenAI. See methodology for more details.
Context window: Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).
Output Speed: Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).
Latency: Time to first token of tokens received, in seconds, after API request sent. For models which do not support streaming, this represents time to receive the completion.
Price: Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).
Output Price: Price per token generated by the model (received from the API), represented as USD per million Tokens.
Input Price: Price per token included in the request/message sent to the API, represented as USD per million Tokens.
Time period: Metrics are 'live' and are based on the past 14 days of measurements, measurements are taken 8 times a day for single requests and 2 times per day for parallel requests.