Groq · small open-weight · Released 2023-06-18

Mixtral Groq 7B: pricing, context window and benchmarks

Mixtral Groq 7B is a small open-weight model from Groq. It offers a 4,096-token context window, costs $0.70 per million input tokens and $2.47 per million output tokens, and averages 53.4 across the index's benchmark suite.

open weightssmall
Input price
$0.70
per 1M tokens
Output price
$2.47
per 1M tokens
Context
4,096
tokens
Avg score
53.4
rank #532 of 600
Arena Elo
1227.8
modelled
Max output
4,096
tokens

Pricing

Mixtral Groq 7B costs $0.70 per million input tokens and $2.47 per million output tokens. A blended 3:1 input-to-output mix works out to about $1.14 per million tokens. Cached input is listed at $0.07 per million tokens.

ItemPriceNotes
Input$0.70per 1M tokens
Output$2.47per 1M tokens
Cached input$0.07per 1M tokens
Blended 3:1$1.14estimate per 1M tokens
1M in + 1M out$3.17estimate

Benchmarks

Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.

BenchmarkScoreRankPercentileRelative
MMLU-Pro 59.3 532 11th
GPQA Diamond 47.5 544 9th
SWE-bench Verified 36.6 545 9th
HumanEval 58.5 519 14th
MATH-500 51.1 546 9th
AIME 2025 43.2 520 13th
LiveCodeBench 43.2 515 14th
IFEval 65.7 525 13th
TruthfulQA 60.1 529 12th
HellaSwag 71.8 504 16th
MMMU 50.2 551 8th
Arena Elo 1227.8 529 12th

What Mixtral Groq 7B is good for

Mixtral Groq 7B is a small model. That makes it a good fit for classification, extraction, routing, summarization and other high-volume jobs where latency and cost dominate. It is not the right pick for open-ended frontier reasoning, but at $0.70 per million input tokens it can handle a large share of production traffic.

Strengths

  • Input price of $0.70 per million tokens is at or below the index median.
  • Open weights make self-hosting, fine-tuning and data-residency review possible.

Trade-offs

  • Context window of 4,096 tokens is small for long-document work.
  • Average benchmark score is below the index median; test it on your own task.
  • Less reliable on open-ended reasoning and complex multi-step instructions.

How it compares

ModelProviderContextInput / 1MAvg score
Qwen3 1.5B Alibaba Cloud 4096 $0.84 53.5
Mixtral Groq 7B Groq 4096 $0.70 53.4
GLM-4.5 1.5B Zhipu AI 16384 $0.65 53.3
Kimi K1.5 1.5B Moonshot AI 4096 $0.75 53.2
Mixtral Turbo 7B Together AI 8192 $0.68 53.2
Llama 4 Scout 1.5B Meta AI 8192 $0.66 53.0

Browse all comparisons →

FAQ

How much does Mixtral Groq 7B cost?

Mixtral Groq 7B is listed at $0.70 per million input tokens and $2.47 per million output tokens. Cached input is $0.075 per million tokens. A blended 3:1 input-to-output mix is about $1.14 per million tokens.

What is the context window of Mixtral Groq 7B?

Mixtral Groq 7B has a context window of 4,096 tokens and can emit up to 4,096 output tokens per request in this index.

Is Mixtral Groq 7B open weights?

Yes. Mixtral Groq 7B is listed as an open-weight model under a open weights licence.

How does Mixtral Groq 7B score on benchmarks?

Mixtral Groq 7B averages 53.4 across the scored benchmarks in this index, ranking #532 of 600 models. Its strongest relative result is Arena Elo at 1227.8.

What is Mixtral Groq 7B best for?

Mixtral Groq 7B is a small model. That makes it a good fit for classification, extraction, routing, summarization and other high-volume jobs where latency and cost dominate. It is not the right pick for open-ended frontier reasoning, but at $0.70 per million input tokens it can handle a large share of production traffic.

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