Models › DeepSeek-V2.5 family

DeepSeek-V2.5-1210

deepseek-ai DeepSeek License (deepseek) out 22 months ago

236B parameters, text in, text out.

Verified 2026-10-25 Rank #772 in LLMs · score 71.1 method v1 Sources 3 Downloads 30d 2.8k · #570 of 619 tracked

Can I run it?141GB at INT4Estimatefits 2×80 GBmethod
Can I use it?DeepSeek License (deepseek)Attribution requiredlicence file
Do people use it?2.8kdownloads, 30 days#570 of 619 we track · below the median+3 likes, downloads +9% this week274 likesHugging Face

Worth reading

Picked by rule from 1 tracked piece: the lab's own post, the most shared, a field report, the latest.

Where it's used

Hugging Face does not say who downloads a model or with what. These are the proxies: API providers listing it, quantized builds, fine-tunes/adapters/merges, and Spaces that load it.

No API provider serves it, so its downloads are people running it themselves: 12 quantized builds.

  • As a service0no API provider listed
  • On own hardware12quantized builds
  • Built on11 fine-tunes · 0 adapters · 0 merges
  • In apps0Hugging Face Spaces

Will it fit?

Weights only, an estimate: leave room for the KV cache. Method

Fits two 80 GB GPUs at INT4; too big for one

About 141 GB at INT4, 283 GB at FP8, 566 GB at BF16: weights only, so leave room for the KV cache. Every expert must be resident, so total parameters count.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 141 GB of weights (estimate; KV cache and activations extra)INT4141 GBFP8: about 283 GB of weights (estimate; KV cache and activations extra)FP8283 GBBF16: about 566 GB of weights (estimate; KV cache and activations extra)BF16566 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 141 GB of weights (estimate; KV cache and activations extra)INT4141 GBFP8: about 283 GB of weights (estimate; KV cache and activations extra)FP8283 GBBF16: about 566 GB of weights (estimate; KV cache and activations extra)BF16566 GB

Estimate params × bytes per param × 1.2 · how we estimate

The story so far

Weights, every dated article, and repo commits on one rail.

1 dated article and 0 repo commits so far

Teal is the weights (2024-12-10), amber triangles are 1 dated article (each links to it).

OctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctDeepSeek v2.5 – open-source LLM comparable to GPT-4, but 95% less expensive · 2024-09-10Weights 2024-12-10 · 2024-12-10Weights 2024-12-10now
OctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctDeepSeek v2.5 – open-source LLM comparable to GPT-4, but 95% less expensive · 2024-09-10Weights 2024-12-10 · 2024-12-10Weights 2024-12-10now

What people built on it

13 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

13 derivatives on the Hub, most of them quantized

From the Hugging Face model tree; quantized builds in teal, fine-tunes, merges and adapters in greys.

12 quantized (Hugging Face model tree)1 fine-tune (Hugging Face model tree)12 quantized1 fine-tune
12 quantized (Hugging Face model tree)1 fine-tune (Hugging Face model tree)12 quantized1 fine-tune

All variants →

Reference

Everything else, folded: the full tables, every source.

Use-case evidence

1 use case

What it is good at 1 use case

Labels are evidence, not verdicts: measured a third-party leaderboard row for this model; author-reported a number the model author published in the card or eval files; structural a deterministic signal from the name, config or chat template, or a decision-model estimate. Each chip links to its source. All use cases.

Facts

15 fields

Listed in LLMs · MoE

Facts

Pipeline tagtext-generation
Librarytransformers
ArchitecturesDeepseekV2ForCausalLM
Model typedeepseek_v2
Params by dtypeBF16: 235,741,434,880
Size bandXXL
MoEyes
Experts per token6
PapersarXiv:2405.04434
LicenseDeepSeek License (deepseek) (other)
Hub snapshot2026-10-25

Hardware fit

3 estimates

Hardware fit ESTIMATE

Weights-only memory for DeepSeek-V2.5-1210: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)566 GB · Multi-GPU node (<640 GB)
FP8 (1 byte/param)283 GB · Multi-GPU node (<640 GB)
INT4 (0.5 bytes/param)141 GB · Multi-GPU node (<640 GB)

Weights only (params × bytes/param × 1.2 overhead); KV cache and activations extra. MoE: all experts must be resident, so total parameters count.

All variants

13 variants

Lineage

Original model Family: deepseek-ai/DeepSeek-V2.5 13 derivatives on the Hub

quantized: 12finetune: 1

Top variants (13 shown, ranked by downloads)

Relation
Quant
Size
13 rows
Variant Relation Quant Params Band License Author Likes Downloads
bartowski/DeepSeek-V2.5-1210-GGUF quantized GGUF — — other bartowski 16 42.7k
mlx-community/DeepSeek-V2.5-1210-4bit quantized -4bit 236B XXL other mlx-community 4 7.8k
lmstudio-community/DeepSeek-V2.5-1210-GGUF quantized GGUF — — other lmstudio-community 5 6.1k
DevQuasar-5/deepseek-ai.DeepSeek-V2.5-1210-GGUF quantized GGUF — — — DevQuasar-5 0 2.8k
adamo1139/DeepSeek-V2.5-1210-AWQ quantized AWQ 236B XXL — adamo1139 3 947
mlx-community/DeepSeek-V2.5-1210-3bit quantized — 236B XXL other mlx-community 2 960
OPEA/DeepSeek-V2.5-1210-int4-sym-inc quantized int4 32.6B L — OPEA 8 526
mlx-community/DeepSeek-V2.5-1210-3bit-32 quantized — 236B XXL other mlx-community 0 482
dong-99/DeepSeek-V2.5-1210-mlx-8Bit quantized mlx 236B XXL other dong-99 0 428
dong-99/DeepSeek-V2.5-1210-mlx-6Bit quantized mlx 236B XXL other dong-99 0 428
AbteeXAILab/lumynax-frontier-coder-deepseek-v25-1210-gguf quantized gguf — — other AbteeXAILab 0 358
mradermacher/DeepSeek-V2.5-1210-i1-GGUF quantized GGUF — — other mradermacher 0 348
mradermacher/DeepSeek-V2.5-1210-GGUF finetune GGUF — — other mradermacher 0 0

Repository changelog

1 change
changed in the last 7 daysNew on the watch list: 2026-10-23all changes

Articles and coverage

1 piece

Ranked by source signals (HN, Lobsters, authority domains, official posts) and recency.

Official1

deepseek.com2024-09-10officialauthorityHN front pageabout the DeepSeek V2.5 familyHN 193 pts · 75 comments38 words

Papers

1 paper

Papers 1

arXiv links found in the model card and its tags. "Peer-reviewed" is shown only with evidence: a published venue in OpenAlex (measured) or the authors' own journal reference on arXiv (reported).

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Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:46 UTC · Summary: 2026-10-14 14:08 UTC · Last verified 2026-10-25

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