DeepSeek V4 Flash 0731
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DeepSeek V4 Flash 0731

Updated Aug 10, 2026
Parameters
304.2B
Context
1,048,576
License
mit
Updated
Aug 10, 2026

Intelligence benchmarks

Artificial Analysis indexes - compared with the best open and proprietary models

Intelligence

51.8

AA Index

Agentic

48.4

AA Index

Intelligence Index - DeepSeek V4 Flash 0731 vs. the field

Best open-weight models (you can run locally) and leading proprietary models for context.

Claude Opus 5 (max)
63.1
closed
Claude Fable 5 (with fallback)
62.1
closed
GPT-5.6 Sol (max)
60.9
closed
Kimi K3
59.7
open
Qwen3.8 Max
58.1
closed
Muse Spark 1.2 (xhigh)
56.8
closed
GLM-5.2
52.6
open
DeepSeek V4 Flash 0731
51.8
open

Agentic Index comparison

Claude Opus 5 (max)
59.2
closed
Qwen3.8 Max
58.4
closed
GPT-5.6 Sol (max)
57.8
closed
Claude Fable 5 (with fallback)
56.6
closed
Kimi K3
54.3
open
GPT-5.6 Terra (max)
50.2
closed
DeepSeek V4 Flash 0731
48.4
open

Benchmark data from Artificial Analysis · updated 2026-08-10.

Standard benchmarks

Performance across standard evaluations

BenchmarkScore
GPQA90.8

Will it run on your hardware?

Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest

Too big for 24 GB at any quant
0 of 4 quantizations fit DeepSeek V4 Flash 0731 with real runtime overhead.
Q5_K_M
216 GB
Q8_0
325 GB
FP16
608 GB
fits tight too big

Need an exact figure for your context length? Use the VRAM calculator.

Run it locally

Copy-paste - running in under a minute

vLLMOpenAI-compatible API
vllm serve deepseek-ai/DeepSeek-V4-Flash-0731

New to this? Start with Ollama · serve to many users with vLLM.

Deep dive

Notes, sources, and the full write-up

DeepSeek V4 Flash 0731 is a 304.2B-parameter mit model from DeepSeek. It scores 49.9 on the Artificial Analysis Intelligence Index (coding 69.1). At Q4_K_M it needs roughly 176 GB of VRAM, placing it in the 48 GB+ / multi-GPU hardware tier.

Benchmarks

Artificial Analysis Intelligence Index - DeepSeek V4 Flash 0731 vs. leading closed models:

ModelIntelligenceCodingGPQA
DeepSeek V4 Flash 073149.969.190.8
Claude Opus 5 (max)60.77893.2
Claude Fable 5 (with fallback)59.976.592.6
GPT-5.6 Sol (max)58.977.494.1
GPT-5.6 Terra (max)5576.792.5
Grok 4.5 (high)53.872.493.1

Source: Artificial Analysis (2026-08-01).

Popularity

DeepSeek V4 Flash 0731 has 0 downloads in the last month on HuggingFace and 1,018 likes.

Frequently asked

Quick answers to common questions

How much VRAM does DeepSeek V4 Flash 0731 need?

DeepSeek V4 Flash 0731 with 304.2B parameters needs approximately 176 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is DeepSeek V4 Flash 0731 better than other deepseek-ai models?

DeepSeek V4 Flash 0731 has 304.2B parameters with 1,048,576 context - a strong choice for general use.

What license is DeepSeek V4 Flash 0731 under?

DeepSeek V4 Flash 0731 is released under the mit license, making it suitable for most commercial and personal projects.

What hardware runs DeepSeek V4 Flash 0731 well?

With 304.2B parameters, DeepSeek V4 Flash 0731 requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.

What is the best quantization for DeepSeek V4 Flash 0731?

Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~216 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.

How long can DeepSeek V4 Flash 0731's context window handle?

DeepSeek V4 Flash 0731 supports a 1,048,576-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.

What models compete with DeepSeek V4 Flash 0731?

DeepSeek V4 Flash 0731 competes with other 152B–456B. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.

Nearby options

Similar models and compatible hardware by spec

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