Can I Run LFM2.5 on NVIDIA GeForce RTX 3080 (10GB)?
作者： Jakub Rusinowski · 最后更新： 2026年9月19日
Yes, comfortably — you'll have ~5 GB of headroom running LFM2.5-8B-A1B at Q4_K_M (5 GB, ~185 tok/s (est.)) with room for up to 16K context.
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NVIDIA GeForce RTX 3080 (10GB) Specs
| VRAM | 10 GB |
| Memory Bandwidth | 760 GB/s |
LFM2.5-8B-A1B on the NVIDIA GeForce RTX 3080 (10GB): VRAM by quantization
| Quant | VRAM needed | Fits 10 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 18 GB | ✗ No | — | — |
| Q8_0 | 10.2 GB | ✗ No | — | — |
| Q6_K | 8.2 GB | ✓ Yes | 16K | — |
| Q5_K_M | 7.3 GB | ✓ Yes | 16K | — |
| Q4_K_M | 6.4 GB | ✓ Yes | 16K | — |
| Q3_K_M | 4.9 GB | ✓ Yes | 32K | — |
| Q2_K | 4.1 GB | ✓ Yes | 32K | — |
Assumes a 4K-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 GB · 32K 10.5 GB ✗ · 128K 24.6 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? LFM2.5-8B-A1B on 16 GB of system RAM, CPU only: runs.
LFM2.5 Sizes That Fit the NVIDIA GeForce RTX 3080 (10GB)
| LFM2.5-8B-A1B | Q4_K_M · 5 GB · ~185 tok/s (est.) |
| LFM2.5 2.6B | Q4_K_M · 1.6 GB · ~153 tok/s (est.) |
At 2 hrs/day, buying (~$699) beats renting at $0.34/hr after about 2.9 years.
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
Is the NVIDIA GeForce RTX 3080 (10GB) enough to run LFM2.5 locally?
Yes, comfortably — you'll have ~5 GB of headroom running LFM2.5-8B-A1B at Q4_K_M (5 GB, ~185 tok/s (est.)) with room for up to 16K context.
What's the best LFM2.5 size for the NVIDIA GeForce RTX 3080 (10GB)?
LFM2.5-8B-A1B at Q4_K_M quantization (5 GB), estimated ~185 tokens/sec, up to 16K context.
LFM2.5 on Other GPUs
- LFM2.5 on Intel Arc B570
- LFM2.5 on NVIDIA GeForce RTX 5070
- LFM2.5 on NVIDIA GeForce RTX 5060 Ti 8GB
- LFM2.5 on NVIDIA GeForce RTX 5060
- LFM2.5 on NVIDIA GeForce RTX 4070 Ti
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VRAM Tier
Troubleshooting
Buying Guide
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