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DeepSeek-V4-Pro (High, 20260813)

deepseek · MIT license · on Arena since 23 Apr 2026

Lab chat Download
Arena score1451#49 of 416 in Chat, paid models included
Size1598.8 B75.6 B active per token (mixture of experts)
4-bit download969 GBweights only, Q4_K_M
Max context1024Ktokens, from the model config

Where to use it for free

Arena scores

ArenaScoreRankVotes
Chat1451#49 of 41658K
Coding1582#33 of 1445K

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 GBDoes not fit—

Estimate at 4-bit with 32K context, 64 GB of DDR5 for offload. Speed ≈ memory bandwidth × 70% ÷ data read per token; real numbers vary by about ±30%.

GPU memory needed

Level8K context32K context128K contextQuality vs full
Q3_K_M801 GB804 GB816 GB+4.7% noticeable loss
Q4_K_M970 GB974 GB986 GB+1.2% very small loss
Q5_K_M1138 GB1141 GB1154 GB+0.4% near-lossless
Q6_K1313 GB1316 GB1328 GB+0.2% near-lossless
Q8_01700 GB1703 GB1716 GB≈ 0% same as full
F163199 GB3202 GB3215 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.

Chat score over time

DeepSeek-V4-Pro (High, 20260813) 1451Best paid model

Arena score from 17 Apr 2026 to 15 Oct 2026.

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