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SambaNova: Models Intelligence, Performance & Price

Analysis of SambaNova'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 SambaNova 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 8B, Llama 3.2 3B, Llama 3.2 1B, Llama 4 Maverick, Llama 4 Scout, DeepSeek R1, DeepSeek R1 Distill Llama 70B, DeepSeek V3 (Mar' 25), and QwQ-32B.
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SambaNova Model Comparison Summary

Intelligence:DeepSeek R1 logo DeepSeek R1 and QwQ-32B logo QwQ-32B are the highest quality models offered by SambaNova, followed by DeepSeek V3 (Mar' 25) logo DeepSeek V3 (Mar' 25), Llama 4 Maverick logo Llama 4 Maverick & DeepSeek R1 Distill Llama 70B logo DeepSeek R1 Distill Llama 70B.Output Speed (tokens/s):Llama 3.2 1B logo Llama 3.2 1B (2590 t/s) and Llama 3.2 3B logo Llama 3.2 3B (1586 t/s) are the fastest models offered by SambaNova, followed by Llama 3.1 8B logo Llama 3.1 8B, Llama 4 Maverick logo Llama 4 Maverick & Llama 4 Scout logo Llama 4 Scout.Latency (seconds):Llama 3.2 1B logo Llama 3.2 1B (0.18s) and  Llama 3.2 3B logo Llama 3.2 3B (0.19s) are the lowest latency models offered by SambaNova, followed by Llama 3.1 8B logo Llama 3.1 8B, Llama 3.3 70B logo Llama 3.3 70B & Llama 4 Maverick logo Llama 4 Maverick.Blended Price ($/M tokens):Llama 3.2 1B logo Llama 3.2 1B ($0.05) and Llama 3.2 3B logo Llama 3.2 3B ($0.10) are the cheapest models offered by SambaNova, followed by Llama 3.1 8B logo Llama 3.1 8B, Llama 4 Scout logo Llama 4 Scout & QwQ-32B logo QwQ-32B.Context Window Size:Llama 3.3 70B logo Llama 3.3 70B (128k) and Llama 3.1 405B logo Llama 3.1 405B (16k) are the largest context window models offered by SambaNova, followed by Llama 3.1 8B logo Llama 3.1 8B, Llama 3.2 1B logo Llama 3.2 1B & DeepSeek R1 logo DeepSeek R1.

Highlights

Intelligence
Artificial Analysis Intelligence 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 Intelligence
Price
Output tokens/s
Latency
End-to-End Response Time
Further
Analysis
SambaNova logo
DeepSeek logo
DeepSeek R1
16k
60
$5.50
191.9
1.80
16.64
12.23
SambaNova logo
Alibaba logo
QwQ-32B
16k
58
$0.63
428.9
1.37
8.34
5.81
SambaNova logo
DeepSeek logo
DeepSeek V3 (Mar' 25)
8k
53
$1.13
264.5
0.62
2.51
N/A
SambaNova logo
Meta logo
Llama 4 Maverick
8k
51
$0.92
778.7
0.54
1.18
N/A
SambaNova logo
DeepSeek logo
DeepSeek R1 Distill Llama 70B
16k
48
$0.88
315.6
1.52
9.44
6.34
SambaNova logo
Meta logo
Llama 4 Scout
8k
43
$0.47
748.4
0.76
1.42
N/A
SambaNova logo
Meta logo
Llama 3.3 70B
128k
41
$0.75
452.1
0.31
1.41
N/A
SambaNova logo
Meta logo
Llama 3.1 405B
16k
40
$6.25
167.6
1.62
4.60
N/A
SambaNova logo
Meta logo
Llama 3.1 8B
16k
24
$0.13
1,173.2
0.24
0.67
N/A
SambaNova logo
Meta logo
Llama 3.2 3B
8k
20
$0.10
1,586.4
0.19
0.51
N/A
SambaNova logo
Meta logo
Llama 3.2 1B
16k
10
$0.05
2,590.2
0.18
0.37
N/A

Key definitions

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): Time to first token received, in seconds, after API request sent. For reasoning models which share reasoning tokens, this will be the first reasoning token. 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 72 hours of measurements, measurements are taken 8 times a day for single requests and 2 times per day for parallel requests.