What is the difference between DeepSeek V4 Flash Vision Exp and Mistral Small 3.1 24B?

DeepSeek V4 Flash Vision Exp (DeepSeek) features Proprietary with a 1000k context window, while Mistral Small 3.1 24B (Mistral AI) features 24B with a 128k context window.

Which is cheaper for production inference, DeepSeek V4 Flash Vision Exp or Mistral Small 3.1 24B?

DeepSeek V4 Flash Vision Exp input pricing is Open / Free per 1M tokens vs Mistral Small 3.1 24B at Open / Free per 1M tokens.

Can I run DeepSeek V4 Flash Vision Exp or Mistral Small 3.1 24B locally on private GPU hardware?

DeepSeek V4 Flash Vision Exp is a closed cloud API and cannot be self-hosted. Mistral Small 3.1 24B is an open-weights model and can be hosted locally.

Back to LLM Benchmark & Hardware Sizing Engine

DeepSeekvsMistral AI

DeepSeek V4 Flash Vision Exp vs Mistral Small 3.1 24B

Side-by-side technical showdown between DeepSeek V4 Flash Vision Exp and Mistral Small 3.1 24B on TheModelverse. Compare verified LLM benchmark scores, quantization compression, local GPU hardware sizing, and API inference pricing.

Executive Showdown & Winner Breakdown

Who Wins Where: DeepSeek V4 Flash Vision Exp vs Mistral Small 3.1 24B

Verified across benchmarks, pricing & local VRAM footprint

Local Portability & Sovereignty

Self-Hostable

Leader:Mistral Small 3.1 24B(Open Weights vs Closed API)

Mistral Small 3.1 24B can be deployed on private GPUs, Ollama, and on-prem clusters without third-party vendor lock-in.

Hardware Sizing & Model Compression

LLM Hardware Sizing & Quantization Sizing

Simulate weight compression levels and dynamic KV-cache expansion to verify whether these models fit on your local hardware or cloud GPU cluster.

Quantization Level

Active Precision

4 bits / parameter

VRAM Reduction

-72.5% vs FP16

Benchmark Retention

96–98% (Sweet Spot)

Context Simulator

Total VRAM Footprint @ 8k Context (INT4 (GGUF / AWQ))

Model 1Cloud Hosted

DeepSeek V4 Flash Vision Exp

Zero Local VRAM

Inference runs fully on provider cloud infrastructure. Zero GPU required locally.

Total Params:

Proprietary

Active Compute:

Dense

Attention Scheme:

MLA (Multi-Head Latent)

Max Context:

1000k tokens

Target Hardware: Zero Local VRAM (Managed Cloud API)

Model 2Open Weights

Mistral Small 3.1 24B

15.3GB

Weights: ~13.2 GBKV Cache: ~0.1 GB+15% CUDA Buffer

Total Params:

24B

Active Compute:

Dense

Attention Scheme:

GQA (Grouped-Query)

Max Context:

128k tokens

Target Hardware: 1x RTX 3090 / 4090 (24GB) or Mac (32GB Unified)

GPU & Hardware Tier Compatibility Matrix

Hardware Configuration	Available VRAM	DeepSeek V4 Flash Vision Exp	Mistral Small 3.1 24B
16 GB VRAM RTX 4070 / 4080 (16GB), Mac M-Series (16GB)	16 GB	Cloud API	Tight (Low Ctx)
24 GB VRAM 1x RTX 3090 / 4090 (24GB), Mac M-Series (32GB)	24 GB	Cloud API	Optimal
48 GB VRAM 2x RTX 4090 (TP=2), 1x L40S, Mac M-Series (64GB)	48 GB	Cloud API	Optimal
80 GB VRAM 1x NVIDIA A100 / H100 (80GB), Mac Studio (128GB)	80 GB	Cloud API	Optimal
160 GB Node 2x H100 (TP=2), 4x L40S, Mac Studio (192GB)	160 GB	Cloud API	Optimal
Multi-Node Cluster 4x–8x H100 Datacenter Cluster	320 GB	Cloud API	Optimal

Inference Economics & Cost Simulator

Token Pricing & Scale Economics

Calculate estimated monthly cloud API spend and evaluate the breakeven point vs self-hosted GPU hardware.

Monthly Queries: 100,000

10k500k1M

Avg Prompt Tokens: 1000

Avg Output Tokens: 300

Pricing Metric	DeepSeek V4 Flash Vision Exp	Mistral Small 3.1 24B
Input Cost (/1M tokens)	Free / Open	Free / Open
Cached Input (/1M tokens)	—	—
Output Cost (/1M tokens)	Free / Open	Free / Open
Simulated Monthly Bill (100,000 calls)	$0 API Cost Open Weights	$0 API Cost Open Weights
Self-Hosted Breakeven vs $864/mo GPU	Self-Hostable Day 1	Self-Hostable Day 1

Architecture Matrix

Feature	DeepSeek V4 Flash Vision Exp	Mistral Small 3.1 24B
Release Date	8/21/2026	3/17/2025
Routing / MoE	Dense	Dense
Attention Mechanism	Standard / GQA	Standard / GQA
Source Type	Proprietary Commercial API	Open Weights (Open)

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