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DeepSeek-V4-Flash

deepseek · MIT license · on Arena since 16 Oct 2026

Lab chat Download
Arena score1432#92 of 417 in Chat, paid models included
Size290.9 B20.4 B active per token (mixture of experts)
4-bit download176 GBweights only, Q4_K_M
Max context1024Ktokens, from the model config

Where to use it for free

Try DeepSeek-V4-Flash now

No account, no payment. 5 questions a day per visitor, short answers. It runs on Cloudflare Workers AI (@cf/deepseek-ai/deepseek-v4-flash-0731). We do not store your question. Do not write personal data.

Arena scores

ArenaScoreRankVotes
Chat1432#92 of 41752K
Coding1582#37 of 1485K

Rank among all models, paid ones included. Source: Arena leaderboard dataset.

Speed on popular hardware

HardwareGPU memoryFits?Speed
RTX 3060 12 GB12 GBDoes not fit—
RTX 4060 Ti 16 GB16 GBDoes not fit—
RTX 309024 GBDoes not fit—
RTX 409024 GBDoes not fit—
RTX 509032 GBDoes not fit—
RX 7900 XTX24 GBDoes not fit—
2 × RTX 309048 GBDoes not fit—
4 × RTX 309096 GBDoes not fit—
Mac M4 Max 128 GB96 GBDoes not fit—
Ryzen AI Max+ 395 128 GB96 GBDoes not fit—
8 × H100 SXM640 GBFits in GPU96 tok/s

Estimate at 4-bit with 32K context, 64 GB of DDR5 for offload. Speed ≈ memory bandwidth × 78% ÷ data read per token, plus a fixed cost per token, calibrated on 44 real llama.cpp tests; typical error about ±10%. Compare all GPUs.

GPU memory needed

Level8K context32K context128K contextQuality vs full
Q3_K_M147 GB149 GB158 GB+4.7% noticeable loss
Q4_K_M178 GB180 GB188 GB+1.2% very small loss
Q5_K_M208 GB210 GB219 GB+0.4% near-lossless
Q6_K240 GB242 GB251 GB+0.2% near-lossless
Q8_0310 GB313 GB321 GB≈ 0% same as full
F16583 GB585 GB594 GB≈ 0% same as full

Weights + context cache (from the model's architecture) + runtime. Quality: increase in perplexity against the full model, from llama.cpp tests, scaled by model size. Simulate your own setup.

Coding score over time

DeepSeek-V4-Flash 1582Best paid model

Arena score from 20 Apr 2026 to 19 Oct 2026.

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