LOADING DATASHEET
LOADING DATASHEET
by DeepSeek
RANKED #75 OF 245 ASSISTANTS · OVERALL #125 OF 6,551 · VIBE SCORE 6.2 · 164 VOICES
DeepSeek-V3.1 Terminus is an update to [DeepSeek V3.1](/deepseek/deepseek-chat-v3.1) that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities, further
8 mentions
5 mentions
26 weeks · 52 voices
HOLDING UP
Recent vibe is steady. No clear fade in the crowd.
Open weights. You can use a hosted service, or download it and run it yourself, free.
Open weights: download DeepSeek V3.1 Terminus once and it's yours. No subscription, no rate limits, works offline.
671B parameters MoE (37B active), a Q4_K_M GGUF is about 404 GB and extreme 2-bit quants are around 220 GB
Custom PC with AMD EPYC 9355 and 256 GB DDR5 RAM
256 GB RAM
~$3500 USED / BUILDToo large for single consumer GPUs. Extreme Q2_K quantization offloaded to system RAM, ~2 to 5 tok/s at 8k context
Apple Mac Studio M2 Ultra (Dual Studio Cluster / 2x 192 GB)
384 GB UNIFIED MEMORY
~$13000 NEWQ3_K_M / Q4_K_S quant, ~10 to 15 tok/s, 32k context comfortably in unified memory
Dedicated 8x NVIDIA RTX 6000 Ada workstation
384 GB VRAM
~$55000 NEWFP8 native precision, high token throughput (40+ tok/s), full 128k context
The three cards above are researched picks. Search the machine you actually have — we only say yes if it should reply at a usable speed, not just load the weights and crawl.
HARDWARE PICKS & PRICES ARE RESEARCHED FROM THE LIVE WEB AND REFRESHED AUTOMATICALLY. TREAT THEM AS BALLPARK, NOT GOSPEL.
Everyday jobs on each of those rigs: how long DeepSeek V3.1 Terminus takes, and how good the crowd says it is at that kind of work.
| THE JOB | BARE MINIMUMCustom PC with AMD EPYC 9355 and 256 GB DDR5 RAM | SWEET SPOTApple Mac Studio M2 Ultra (Dual Studio Cluster / 2x 192 GB) | FULL POWERDedicated 8x NVIDIA RTX 6000 Ada workstation |
|---|---|---|---|
| Write an emaila paragraph or two, drafted from a one-line brief | ~2.4 MIN★★★★★ | ~40 S★★★★★ | —★★★★★ |
| Summarize a documenta long report boiled down to the points that matter | ~7.1 MIN★★★★★ | ~2 MIN★★★★★ | —★★★★★ |
| Build a websitea small landing page, markup and styles together | ~38 MIN★★★★★ | ~11 MIN★★★★★ | —★★★★★ |
| Build a backendan API with routes, storage and tests | ~2 HR★★★★★ | ~33 MIN★★★★★ | —★★★★★ |
| Build a gamea playable browser game in one file | ~71 MIN★★★★★ | ~20 MIN★★★★★ | —★★★★★ |
STARS ARE THE COMMUNITY SCORE FOR THAT KIND OF WORK, DOCKED FOR HOW SQUASHED THE WEIGHTS GET AT EACH TIER. A DASH MEANS NO SPEED WAS RESEARCHED FOR THAT RIG. TIMES ARE COMPUTED FROM RESEARCHED SPEEDS. BALLPARK, NOT GOSPEL.
The internet is split on DeepSeek V3.1 Terminus. Biggest praise: price. Biggest gripe: getting facts right.
99 POSTS · 65 COMMENTS · LEMMY · REDDIT · DEV FORUMS · GITHUB · BLOG
5 thumbs up · 2 thumbs down
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Checked picks first: tags say why you would switch, stars say how fully each one stands in for DeepSeek V3.1 Terminus.
Ollama Models Ranked by VRAM Requirements
DeepSeek v3.1 just went live on HuggingFace
Kimi K2: New SoTA non-reasoning model 1T parameters open-source and outperforms DeepSeek-v3.1 and GPT-4.1 by a large margin
Your local Ollama agents can be just as good as closed-source models - I open-sourced Stanford's ACE framework that makes agents learn from mistakes
You can now run DeepSeek-V3.1-Terminus locally!
DeepSeek-V3.1-Terminus
Deepseek released Deepseek V3.1 Terminus
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