GLM-5-FP8 vs DeepSeek-V3.2

Specs, VRAM requirements and download trends — updated 10 November 2026.

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

Specification comparison

Differences are highlighted; identical values are muted.

Specification GLM-5-FP8 DeepSeek-V3.2
Deployment Open weights Open weights · also via API
Parameters 753.9 B 685.4 B
Architecture GlmMoeDsaForCausalLM DeepseekV32ForCausalLM
Context length 202,752 163,840
Licence mit mit
Commercial use Allowed Allowed
Languages 2 —
Downloads 30d 202,976 7,616,440
Downloads all time 13.0 M 35.7 M
Quantizations on the Hub SAFETENSORS SAFETENSORS
Gated No No
First seen on the Hub 2026-02-11 2025-12-01
API input price / 1M tokens not on OpenRouter $0.26
API output price / 1M tokens not on OpenRouter $0.38
Est. cost per 1M input + 1M output tokens not on OpenRouter $0.64
Cached input / 1M tokens not on OpenRouter $0.13
AA Intelligence Index not on OpenRouter —
AA Coding Index not on OpenRouter 44.2
AA Agentic Index not on OpenRouter —
Max output tokens not on OpenRouter 147,456
API providers not on OpenRouter 7
Tool calling not on OpenRouter Yes
Reasoning mode not on OpenRouter Yes

API cost

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

DeepSeek-V3.2 $0.64

Download trend

Daily snapshots, last 90 days (13 Aug – 10 Nov)

7.6 M203 K
GLM-5-FP8 DeepSeek-V3.2

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-FP8 · fp16 @ 198K ctx 3,631.2 GB / 24 GB
❌ Won’t fit

Adjacent comparisons