โ† Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

Mixtral 8x22B vs Step 3.7 Flash

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Mixtral 8x22B and Step 3.7 Flash.

Mistral

Mixtral 8x22B

Mixtral 8x22B is Mistral AI's open-weight Mixture-of-Experts model, activating only 39B of its 141B total parameters per token to deliver frontier-level performance at inference costs comparable to a much smaller dense model. Released under the Apache 2.0 license, Mixtral 8x22B is one of the most capable fully open-weight models available, with strong multilingual performance, robust coding ability, and efficient fine-tuning via LoRA. It is widely deployed across self-hosted infrastructure, including Ollama, vLLM, and Hugging Face TGI.

View Full Specs
StepFun

Step 3.7 Flash

Step 3.7 Flash is StepFun's latest high-efficiency multimodal Mixture-of-Experts model. It pairs a 196B-parameter language backbone with a vision encoder for native image and video understanding, activating roughly 11B parameters...

View Full Specs

Technical Specifications

SpecificationMixtral 8x22BStep 3.7 Flash
ProviderMistralStepFun
Context Window65,536 tokens256,000 tokens
Agent Suitability87/100N/A
Time to First Token (TTFT)320 msN/A
Deployment Modelself hostablemanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-12-112026-05-28

API Pricing Comparison

Input Price per Million Tokens

Mixtral 8x22B

$0.50

Step 3.7 Flash

$0.20

Output Price per Million Tokens

Mixtral 8x22B

$1.00

Step 3.7 Flash

$1.15

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
N/Avs8450.0%
Mixtral 8x22B
Step 3.7 Flash
HumanEvalPython coding & logic synthesis
N/Avs8600.0%
Mixtral 8x22B
Step 3.7 Flash
MATHComplex mathematical problem solving
N/Avs6680.0%
Mixtral 8x22B
Step 3.7 Flash
GPQAGraduate-level expert reasoning
N/Avs4400.0%
Mixtral 8x22B
Step 3.7 Flash
HellaSwagCommonsense reasoning and inference
N/Avs8580.0%
Mixtral 8x22B
Step 3.7 Flash
MT-BenchMulti-turn conversation flow quality
N/Avs890.0%
Mixtral 8x22B
Step 3.7 Flash

Mixtral 8x22B Quirks & Gotchas

  • โ–ธMoE architecture โ€” efficient inference for its capability tier
  • โ–ธRequires ~90GB VRAM at FP16 โ€” 4-bit quantization recommended for single-GPU deployment

Step 3.7 Flash Quirks & Gotchas

No developer gotchas reported.