← Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

Mixtral 8x22B vs Nano Banana 2 (Gemini 3.1 Flash Image)

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 Nano Banana 2 (Gemini 3.1 Flash Image).

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
Google

Nano Banana 2 (Gemini 3.1 Flash Image)

Gemini 3.1 Flash Image, a.k.a. "Nano Banana 2," is Google’s latest state of the art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines advanced...

View Full Specs

Technical Specifications

SpecificationMixtral 8x22BNano Banana 2 (Gemini 3.1 Flash Image)
ProviderMistralGoogle
Context Window65,536 tokens131,072 tokens
Agent Suitability87/100N/A
Time to First Token (TTFT)320 msN/A
Deployment Modelself hostablemanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-12-112026-06-18

API Pricing Comparison

Input Price per Million Tokens

Mixtral 8x22B

$0.50

Nano Banana 2 (Gemini 3.1 Flash Image)

$0.50

Output Price per Million Tokens

Mixtral 8x22B

$1.00

Nano Banana 2 (Gemini 3.1 Flash Image)

$3.00

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.

Mixtral 8x22B Quirks & Gotchas

  • MoE architecture — efficient inference for its capability tier
  • Requires ~90GB VRAM at FP16 — 4-bit quantization recommended for single-GPU deployment

Nano Banana 2 (Gemini 3.1 Flash Image) Quirks & Gotchas

No developer gotchas reported.