DeepSeek-V3.2 vs GLM-5.1-FP8

Specs, VRAM requirements and download trends — updated 25 October 2026.

deepseek-ai · A · Open weights
Params
685.4 B
Context
163,840
30d
5.6 M
mit · commercial OK
zai-org · B · Open weights
Params
753.9 B
Context
202,752
30d
200 K
mit · commercial OK

Specification comparison

Differences are highlighted; identical values are muted.

Specification DeepSeek-V3.2 GLM-5.1-FP8
Deployment Open weights · also via API Open weights
Parameters 685.4 B 753.9 B
Architecture DeepseekV32ForCausalLM GlmMoeDsaForCausalLM
Context length 163,840 202,752
Licence mit mit
Commercial use Allowed Allowed
Languages — 2
Downloads 30d 5,571,243 200,338
Downloads all time 30.7 M 4.1 M
Quantizations on the Hub SAFETENSORS SAFETENSORS
Gated No No
First seen on the Hub 2025-12-01 2026-04-03
API input price / 1M tokens $0.28 not on OpenRouter
API output price / 1M tokens $0.42 not on OpenRouter
Est. cost per 1M input + 1M output tokens $0.70 not on OpenRouter
Cached input / 1M tokens $0.028 not on OpenRouter
AA Intelligence Index 21.5 not on OpenRouter
AA Coding Index 44.2 not on OpenRouter
AA Agentic Index — not on OpenRouter
Max output tokens 65,536 not on OpenRouter
API providers 11 not on OpenRouter
Tool calling Yes not on OpenRouter
Reasoning mode Yes not on OpenRouter

API cost

Estimated cost of 1M input + 1M output tokens via OpenRouter

DeepSeek-V3.2 $0.70

Download trend

Daily snapshots, last 90 days (28 Jul – 25 Oct)

5.6 M200 K
DeepSeek-V3.2 GLM-5.1-FP8

VRAM side by side

On RTX 4090 · 24 GB · 8K context unless noted

DeepSeek-V3.2 · fp16 @ 160K ctx 2,815.1 GB / 24 GB
❌ Won’t fit
GLM-5.1-FP8 · fp16 @ 198K ctx 3,631.2 GB / 24 GB
❌ Won’t fit

Adjacent comparisons