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xAI: Models Quality, Performance & Price

Analysis of xAI'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 xAI for your use-case. For more details including relating to our methodology, see our FAQs. Models analyzed: Grok Beta.
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x.ai Model Comparison Summary

Quality:Grok Beta logo Grok Beta is the highest quality model offered by x.ai with a quality index of 70.4.Output Speed (tokens/s):Grok Beta logo Grok Beta is the fastest model offered by x.ai with a output speed of 57 tokens per second.Latency (seconds):Grok Beta logo Grok Beta is the lowest latency model offered by x.ai with a time to first token of 0.45 seconds.Blended Price ($/M tokens):Grok Beta logo Grok Beta is the cheapest model offered by x.ai with a blended price of 7.50.Context Window Size:Grok Beta logo Grok Beta supports the largest context window of 8k tokens offered by x.ai.

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:
Note: Long prompts not supported as a context window of at least 10k tokens is required

Quality vs. Output Speed, Price

Artificial Analysis Quality Index; Output Speed: Output Tokens per Second; Price: Price: USD per 1M Tokens
Most attractive quadrant
Size represents Price (USD per M Tokens)
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.
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).
Price: Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).

Function Calling Support

ModelsFunction callingJSON Mode
Grok Beta, x.ai logoGrok Beta, x.ai
Function (Tool) Calling: Indicates whether the provider supports function calling in their API. Function calling is also known as 'Tool Calling'.
JSON Mode: Indicates whether the provider supports JSON mode in their API. When JSON mode is enabled, the models will always return a valid JSON object.

Quality & Context Window

Quality Evaluations

Evaluation results measured independently by Artificial Analysis; Higher is better
Artificial Analysis Quality Index
Reasoning & Knowledge (MMLU)
Scientific Reasoning & Knowledge (GPQA)
Quantitative Reasoning (MATH)
Coding (HumanEval)
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.

Quality vs. Context Window, Input Token Price

Artificial Analysis Quality Index; Context Window: Tokens Limit; Input Price: USD per 1M Input Tokens
Most attractive quadrant
Size represents Input Price (USD per M Input Tokens)
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).
Input price: Price per token included in the request/message sent to the API, represented as USD per million Tokens.

Context Window

Context Window: Tokens Limit; Higher is better
Context window: Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

Quality vs. Price

Artificial Analysis Quality Index; Price: Price: USD per 1M Tokens
Most attractive quadrant
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.
Price: Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).
Median across providers: Figures represent median (P50) across all providers which support the model.

Pricing: Input and Output Prices

Price: USD per 1M Tokens
Input price
Output price
Input price: Price per token included in the request/message sent to the API, represented as USD per million Tokens.
Output price: Price per token generated by the model (received from the API), represented as USD per million Tokens.
Median across providers: Figures represent median (P50) across all providers which support the model.

Performance Summary

Output Speed vs. Price

Output Speed: Output Tokens per Second; Price: Price: USD per 1M Tokens
Most attractive quadrant
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).
Price: Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).

Latency vs. Output Speed

Latency: Seconds to First Tokens Chunk Received; Output Speed: Output Tokens per Second
Most attractive quadrant
Size represents Price (USD per M Tokens)
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).
Median across providers: Figures represent median (P50) across all providers which support the model.

Speed

Measured by Output Speed (tokens per second)

Output Speed

Output Tokens per Second; Higher is better
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).
Median across providers: Figures represent median (P50) across all providers which support the model.

Output Speed by Input Token Count (Context Length)

Output Tokens per Second; Higher is better
100 input tokens
1k input tokens
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).
Input Tokens Length: Length of tokens provided in the request. See Prompt Options above to see benchmarks of different input prompt lengths across other charts.
Median across providers: Figures represent median (P50) across all providers which support the model.

Output Speed Variance

Output Tokens per Second; Results by percentile; Higher is better
Median, Other points represent 5th, 25th, 75th, 95th Percentiles respectively
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).
Boxplot: Shows variance of measurements
Picture of the author

Output Speed, Over Time

Output Tokens per Second; Higher is better
Smaller, emerging providers offer high output speed, though precise speeds delivered vary day-to-day.
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).
Over time measurement: Median measurement per day, based on 8 measurements each day at different times. Labels represent start of week's measurements.

Latency

Measured by Time (seconds) to First Token

Latency

Seconds to First Tokens Chunk Received; Lower is better
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.
Median across providers: Figures represent median (P50) across all providers which support the model.

Latency by Input Token Count (Context Length)

Seconds to First Tokens Chunk Received; Lower is better
100 input tokens
1k input tokens
Input Tokens Length: Length of tokens provided in the request. See Prompt Options above to see benchmarks of different input prompt lengths across other charts.
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.
Median across providers: Figures represent median (P50) across all providers which support the model.

Latency Variance

Seconds to First Tokens Chunk Received; Results by percentile; Lower is better
Median, Other points represent 5th, 25th, 75th, 95th Percentiles respectively
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.
Boxplot: Shows variance of measurements
Picture of the author

Latency, Over Time

Seconds to First Tokens Chunk Received; Lower is better
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.
Over time measurement: Median measurement per day, based on 8 measurements each day at different times. Labels represent start of week's measurements.

Total Response Time

Time to receive 100 tokens output, calculated from latency and output speed metrics

Total Response Time

Seconds to Output 100 Tokens; Lower is better
Total Response Time: Time to receive a 100 token response. Calculated based on Latency (time to receive first token) and Output Speed (output tokens per second).
Median across providers: Figures represent median (P50) across all providers which support the model.

Total Response Time by Input Token Count (Context Length)

Seconds to Output 100 Tokens; Lower is better
100 input tokens
1k input tokens
Input Tokens Length: Length of tokens provided in the request. See Prompt Options above to see benchmarks of different input prompt lengths across other charts.
Total Response Time: Time to receive a 100 token response. Calculated based on Latency (time to receive first token) and Output Speed (output tokens per second).
Median across providers: Figures represent median (P50) across all providers which support the model.

Total Response Time Variance

Total: Response Time: Seconds to Output 100 Tokens; Results by percentile; Lower is better
Median, Other points represent 5th, 25th, 75th, 95th Percentiles respectively
Total Response Time: Time to receive a 100 token response. Calculated based on Latency (time to receive first token) and Output Speed (output tokens per second).
Boxplot: Shows variance of measurements
Picture of the author

Total Response Time, Over Time

Seconds to Output 100 Tokens; Lower is better
Total Response Time: Time to receive a 100 token response. Calculated based on Latency (time to receive first token) and Output Speed (output tokens per second).
Over time measurement: Median measurement per day, based on 8 measurements each day at different times. Labels represent start of week's measurements.
Features
Price
Output tokens/s
Latency
Further
Analysis
xAI logo
xAI logo
Grok Beta
8k
70
$7.50
57.0
0.45

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.