Can I Run GLM-4.7 / GLM-Z1 on NVIDIA GeForce RTX 3080 (10GB)?
Written by Jakub Rusinowski · Last updated August 15, 2026
Yes, comfortably — GLM-4 9B at Q4_K_M needs 7.4 GB at 8K context (5.4 GB weights + 2 GB KV cache/overhead), leaving ~2.6 GB of the NVIDIA GeForce RTX 3080 (10GB)'s 10 GB, at ~67 tok/s (est.), with room for up to 16K context.
See what else this hardware can run →
or compare on Vast.ai from $0.35/hr (typical low · varies)
As an Amazon Associate we earn from qualifying purchases. Cloud GPU links are referral links — we may earn a commission at no extra cost to you.
NVIDIA GeForce RTX 3080 (10GB) Specs
| VRAM | 10 GB |
| Memory Bandwidth | 760 GB/s |
GLM-4 9B on the NVIDIA GeForce RTX 3080 (10GB): VRAM by quantization
| Quant | VRAM needed | Fits 10 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 20 GB | ✗ No | — | — |
| Q8_0 | 11.6 GB | ✗ No | — | — |
| Q6_K | 9.4 GB | ✓ Yes | 8K | — |
| Q5_K_M | 8.4 GB | ✓ Yes | 16K | — |
| Q4_K_M | 7.4 GB | ✓ Yes | 16K | — |
| Q3_K_M | 5.8 GB | ✓ Yes | 32K | — |
| Q2_K | 5 GB | ✓ Yes | 32K | — |
Assumes an 8K-token context with an f16 KV cache, on an estimated architecture — this model publishes no config we can read. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 10 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the NVIDIA GeForce RTX 3080 (10GB): 8K 7.4 GB · 32K 11.1 GB ✗ · 125K 25.1 GB ✗. Past 32K it no longer fits 10 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? GLM-4 9B on 8 GB of system RAM, CPU only: runs, but it is tight.
GLM-4.7 / GLM-Z1 Sizes That Fit the NVIDIA GeForce RTX 3080 (10GB) (at 8K context)
| GLM-4 9B | Q4_K_M · 7.4 GB at 8K context · ~67 tok/s (est.) |
At 2 hrs/day, buying (~$699) beats renting at $0.34/hr after about 2.9 years.
Affiliate links — we may earn a commission if you sign up, at no extra cost to you.
Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
GLM-4.7 / GLM-Z1 on the NVIDIA GeForce RTX 3080 (10GB) — does it fit?
Yes, comfortably — GLM-4 9B at Q4_K_M needs 7.4 GB at 8K context (5.4 GB weights + 2 GB KV cache/overhead), leaving ~2.6 GB of the NVIDIA GeForce RTX 3080 (10GB)'s 10 GB, at ~67 tok/s (est.), with room for up to 16K context.
Which GLM-4.7 / GLM-Z1 variant fits best on the NVIDIA GeForce RTX 3080 (10GB)?
GLM-4 9B at Q4_K_M quantization needs 7.4 GB at 8K context (5.4 GB weights + 2 GB KV cache/overhead), estimated ~67 tokens/sec, up to 16K context.
Every GLM-4.7 / GLM-Z1 size on the NVIDIA GeForce RTX 3080 (10GB)
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| GLM-Z1 32B (Reasoning) | 22 GB | Does not fit | — |
| GLM-4.7-Flash 30B-A3B | 20.7 GB | Does not fit | — |
| GLM-4 9B | 7.4 GB | Runs | ~67 tok/s |
GLM-4.7 / GLM-Z1 on Other GPUs
- GLM-4.7 / GLM-Z1 on Intel Arc B570
- GLM-4.7 / GLM-Z1 on NVIDIA GeForce RTX 5070
- GLM-4.7 / GLM-Z1 on NVIDIA GeForce RTX 5060 Ti 8GB
- GLM-4.7 / GLM-Z1 on NVIDIA GeForce RTX 5060
- GLM-4.7 / GLM-Z1 on NVIDIA GeForce RTX 4070 Ti
Popular Models on the NVIDIA GeForce RTX 3080 (10GB)
- DeepSeek R1 on NVIDIA GeForce RTX 3080 (10GB)
- Qwen 3 on NVIDIA GeForce RTX 3080 (10GB)
- Qwen 2.5 Family on NVIDIA GeForce RTX 3080 (10GB)
VRAM Tier
Troubleshooting
Buying Guide
← Can I Run It? | GLM-4.7 / GLM-Z1 Model Page | NVIDIA GeForce RTX 3080 (10GB) GPU Page | VRAM calculator | Check Your Hardware