All Models/grok-code-fast-1
Benchmark:77.8
Speed:Fast

Specs & Pricing

API pricing per 1M tokens and core technical specifications
๐Ÿ“ฅ
Input / 1M
$0.2000
๐Ÿ“ค
Output / 1M
$1.5000
โšก
Cache Price / 1M
$0.0200
๐Ÿ“
Context Window
256K
256,000 tokens
๐Ÿ“
Max Output
-
-
๐ŸŽฏ
Benchmark & Speed
77.8
Speed:Fast

Cost Calculator

Simulate estimated API usage cost based on your specific traffic and context size

Calculation Settings

Pricing Tier
โ–ถ Detailed Settings
โ–ถ Presets

Simulation Results

Input Cost$0.0020
Output Cost$0.0045
Cache Cost$0.0002
Total$0.0067
Saved: $0.0018

Calculation Details

INPUT
(1,024 / 1M) ร— $0.2 + 10req ร— (976 / 1M) ร— $0.2 = $0.0020
OUTPUT
10req ร— (300 / 1M) ร— $1.5 = $0.0045
CACHE
Read: 9req ร— (1,024 / 1M) ร— $0.02 = $0.0002

Alternative Models

Models with comparable benchmark score and pricing tier
ModelProviderContext WindowMax OutputTraining CutoffInput / 1MCache Price / 1MOutput / 1MBenchmarkSpeedTotal
OpenAI๐Ÿ‘‘
1M128K2026-02$0.20$0.02$1.2088Blazing Fast$0.0060
DeepSeek๐Ÿ‘‘
1M384K-$0.30$0.006$1.2086.5Blazing Fast$0.0066
OpenAI๐Ÿ‘‘
400K128K2025-08$0.20$0.02$1.2577.5Blazing Fast$0.0059
Google๐Ÿ‘‘
1M65K2025-01$0.25$0.025$1.5074.25Blazing Fast$0.0085
OpenAI
1M32K2024-06$0.40$0.10$1.6068.75Fast$0.0097

Provider

OpenAI๐Ÿ‘‘

Benchmark

88

Speed

Blazing Fast

Training Cutoff

2026-02

Context Window

1M

Max Output

128K

Input / 1M

$0.20

Cache Price / 1M

$0.02

Output / 1M

$1.20

Total๏ผˆ่ฉฆ็ฎ—๏ผ‰
In: $0.0020 / Out: $0.0036
$0.0060

Provider

DeepSeek๐Ÿ‘‘

Benchmark

86.5

Speed

Blazing Fast

Training Cutoff

-

Context Window

1M

Max Output

384K

Input / 1M

$0.30

Cache Price / 1M

$0.006

Output / 1M

$1.20

Total๏ผˆ่ฉฆ็ฎ—๏ผ‰
In: $0.0029 / Out: $0.0036
$0.0066

Provider

OpenAI๐Ÿ‘‘

Benchmark

77.5

Speed

Blazing Fast

Training Cutoff

2025-08

Context Window

400K

Max Output

128K

Input / 1M

$0.20

Cache Price / 1M

$0.02

Output / 1M

$1.25

Total๏ผˆ่ฉฆ็ฎ—๏ผ‰
In: $0.0020 / Out: $0.0037
$0.0059

Provider

Google๐Ÿ‘‘

Benchmark

74.25

Speed

Blazing Fast

Training Cutoff

2025-01

Context Window

1M

Max Output

65K

Input / 1M

$0.25

Cache Price / 1M

$0.025

Output / 1M

$1.50

Total๏ผˆ่ฉฆ็ฎ—๏ผ‰
In: $0.0024 / Out: $0.0045
$0.0085

Provider

OpenAI

Benchmark

68.75

Speed

Fast

Training Cutoff

2024-06

Context Window

1M

Max Output

32K

Input / 1M

$0.40

Cache Price / 1M

$0.10

Output / 1M

$1.60

Total๏ผˆ่ฉฆ็ฎ—๏ผ‰
In: $0.0039 / Out: $0.0048
$0.0097
โšก Main Feature

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grok-code-fast-1 Frequently Asked Questions (FAQ)

Key insights into grok-code-fast-1 API pricing, context capacity, caching savings, and performance benchmarks

Q. What is the API pricing for grok-code-fast-1? How much does it cost per 1M tokens?๏ผ‹

grok-code-fast-1 (xAI) is priced at $0.2000 per 1 million input tokens and $1.5000 per 1 million output tokens. The output rate is approximately 7.5x higher than the input rate. You can simulate your exact monthly API expenses tailored to your request volume and token length using the calculator above.

Q. What are the context window and maximum output limits of grok-code-fast-1?๏ผ‹

grok-code-fast-1 features a 256K context window and a maximum output limit of - tokens per request. It provides ample capacity for multi-turn dialogs and complex document parsing.

Q. Does grok-code-fast-1 support Prompt Caching, and how much cost can be saved?๏ผ‹

Yes, grok-code-fast-1 supports prompt caching. Cached reads cost $0.0200 per 1M tokens, delivering an estimated 90% discount compared to standard input rates. Caching reusable system instructions and documentation substantially lowers recurring API expenses.

Q. What is the benchmark score (77.75) and performance profile of grok-code-fast-1?๏ผ‹

grok-code-fast-1 achieves an overall benchmark score of 77.75/100 with a "Fast" speed rating. It strikes an optimal tradeoff between high analytical capability, speed, and affordability.

Q. Which alternative models are comparable to grok-code-fast-1?๏ผ‹

Key alternatives in similar price-to-performance tiers include GPT-5.6 Luna, DeepSeek-V4.1-Flash, GPT-5.4 nano. We recommend comparing them based on your latency targets, context window needs, and prompt caching benefits using the full comparison tool on this site.