FITMYLLM · NOVEMBER 4, 2026 · OPEN METHODOLOGY · COMMUNITY BENCHMARKS
LIVE · UPDATED DAILY
763.21B
Parameters (16B active)
Quantization Options Select your GPU for speed estimates Context length: 4K 8K 16K 32K 64K 128K 256K 512K 1M
Quant Bits VRAM @ 16K Quality IQ2_XXS 2.38 227.6 GB
227.5 + 0.0 KV
low IQ2_M 2.93 280.1 GB
280.0 + 0.0 KV
low Q2_K 3.16 302.0 GB
302.0 + 0.0 KV
low IQ3_XXS 3.25 310.6 GB
310.5 + 0.0 KV
low IQ3_XS 3.5 334.4 GB
334.4 + 0.0 KV
low Q3_K_S 3.64 347.8 GB
347.7 + 0.0 KV
low IQ3_M 3.76 359.2 GB
359.2 + 0.0 KV
low Q3_K_M 4 382.1 GB
382.1 + 0.0 KV
low Q3_K_L 4.3 410.8 GB
410.7 + 0.0 KV
moderate IQ4_XS 4.46 426.0 GB
426.0 + 0.0 KV
moderate Q4_K_S 4.67 446.0 GB
446.0 + 0.0 KV
moderate Q4_K_M 4.89 467.0 GB
467.0 + 0.0 KV
good Q5_K_S 5.57 531.9 GB
531.9 + 0.0 KV
good Q5_K_M 5.7 544.3 GB
544.3 + 0.0 KV
good Q6_K 6.56 626.4 GB
626.3 + 0.0 KV
excellent Q8_0 8.5 811.4 GB
811.4 + 0.0 KV
lossless FP16 16 1526.9 GB
1526.9 + 0.0 KV
lossless
Select your GPU above to see speed estimates and compatibility for each quantization.
Too big for a single GPU — plan a multi-GPU deployment
Even the lightest quant needs ~228 GB. Size GPUs, replicas, TCO and scaling for a production setup. Open in Enterprise →
▸ READY TO RUN THIS? RENT BY THE HOUR
RENT A GPU AND RUN DEEPSEEK V4.1 FLASH 1017 NOW
Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.
Community Ratings Chat Coding Reasoning Creative Vision Roleplay Agentic
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Run this model IQ2_XXS — 227.5 GB VRAM IQ2_M — 280.0 GB VRAM Q2_K — 302.0 GB VRAM IQ3_XXS — 310.5 GB VRAM IQ3_XS — 334.4 GB VRAM Q3_K_S — 347.7 GB VRAM IQ3_M — 359.2 GB VRAM Q3_K_M — 382.1 GB VRAM Q3_K_L — 410.7 GB VRAM IQ4_XS — 426.0 GB VRAM Q4_K_S — 446.0 GB VRAM Q4_K_M — 467.0 GB VRAM Q5_K_S — 531.9 GB VRAM Q5_K_M — 544.3 GB VRAM Q6_K — 626.3 GB VRAM Q8_0 — 811.4 GB VRAM FP16 — 1526.9 GB VRAM
Ollama llama.cpp vLLM LM Studio KoboldCpp Jan Docker
▸ Easiest way to get started · Beginners
DOCS ↗ curl -fsSL https://ollama.com/install.sh | shCOPY
$ ollama run deepseek:763b-q4_K_MCOPY
Tag may need adjustment — check ollama.com/library/deepseek for available tags.
▸ SETUP GUIDE >_
Auto-setup with fitmyllm CLI Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.
Auto-detect GPU Live tok/s in chat Speed benchmarks 9 inference engines
Find the best GPU for DeepSeek V4.1 Flash 1017
Build Hardware for DeepSeek V4.1 Flash 1017 ▸ COLOPHON FITMYLLM · INDEPENDENT · DATA-DRIVEN
FITMYLLM · EST. 2025 · © 2026
RECOMMENDATIONS FROM PUBLISHED MATH, CORRECTED BY THE COMMUNITY — 30.
▸ SPEC SHEET
DeepSeek V4.1 Flash 1017 — 763.21B MoE. ▸ SPECIFICATIONS
PARAMETERS 763.21B (16B active)
ARCHITECTURE Mixture of Experts
CONTEXT LENGTH 1024K tokens
CAPABILITIES chat, coding, reasoning, multilingual, vision, math, agentic, tool_use
RELEASE DATE 2026-10-17
PROVIDER DeepSeek
FAMILY deepseek ▸ VRAM REQUIREMENTS
QUANT BPW VRAM QUALITY IQ2_XXS 2.38 227.5 GB 65% IQ2_M 2.93 280.0 GB 75% Q2_K 3.16 302.0 GB 78% IQ3_XXS 3.25 310.5 GB 82% IQ3_XS 3.5 334.4 GB 84% Q3_K_S 3.64 347.7 GB 85% IQ3_M 3.76 359.2 GB 86% Q3_K_M 4 382.1 GB 88% Q3_K_L 4.3 410.7 GB 90% IQ4_XS 4.46 426.0 GB 92% Q4_K_S 4.67 446.0 GB 93% Q4_K_M 4.89 467.0 GB 94% Q5_K_S 5.57 531.9 GB 96% Q5_K_M 5.7 544.3 GB 96% Q6_K 6.56 626.3 GB 97% Q8_0 8.5 811.4 GB 100% FP16 16 1526.9 GB 100%
§ 01 BENCHMARK SCORES
HLE 43.3
aa_scicode 55.9
aa_lcr 82.7
aa_terminal_bench_v4 33.8
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