RTX 5080 vs RTX 4090 for local AI (2026)
VRAM, memory bandwidth, today's prices (new, used and rental) and which local AI models each card can run.
Prices updated Nov 12, 2026The short version
- VRAM: the RTX 4090 has 8 GB more, so it fits bigger models: at Q4 it runs Qwen3 32B, Qwen3 30B-A3B (MoE), Qwen2.5 Coder 32B Instruct, Gemma 3 27B IT, which the RTX 5080 can't.
- Speed: the RTX 4090 has about 5% more memory bandwidth, so expect roughly 5% faster token generation on models that fit both (estimate; prompt processing and image generation depend on compute, not shown).
- Price: the RTX 5080 is $1,187 cheaper today ($1,879 used vs $3,066 used); per GB of VRAM that's $117 vs $128.
- Renting: RTX 5080 from $0.19/hr, RTX 4090 from $0.34/hr. Try both by the hour before you buy.
Specs and prices
| RTX 5080 | RTX 4090 | |
|---|---|---|
| VRAM | 16 GB GDDR7 | 24 GB GDDR6X |
| Memory bandwidth | 960 GB/s | 1,008 GB/s |
| Memory bus | 256-bit | 384-bit |
| Cheapest today | $1,879 usedGPU Sold · 2026-11-10 | $3,066 usedGPU Sold · 2026-11-10 |
| Lowest new | $2,000ByteSizedDeals | — |
| Used (median eBay ask) | $1,879GPU Sold | $3,066GPU Sold |
| $ per GB VRAM | $117 | $128 |
| Rent from | $0.19/hrVast.ai | $0.34/hrRunpod |
| Launch MSRP | $999 | $1,599 |
| Launched | 2025-01 | 2022-10 |
| Software | CUDA - best support in llama.cpp, vLLM, ComfyUI | CUDA - best support in llama.cpp, vLLM, ComfyUI |
| Check priceused · eBayor new on Amazon | Check priceused · eBayor new on Amazon |
Which models fit
| Model | RTX 5080 Q4 | RTX 4090 Q4 | RTX 5080 Q8 | RTX 4090 Q8 |
|---|---|---|---|---|
| Llama 3.1 8B Instruct | ✓ ~96 tok/s6.5 GB | ✓ ~101 tok/s6.5 GB | ✓ ~59 tok/s9.9 GB | ✓ ~62 tok/s9.9 GB |
| Llama 3.3 70B Instruct | ✗needs 43 GB | ✗needs 43 GB | ✗needs 73 GB | ✗needs 73 GB |
| Qwen3 8B | ✓ ~93 tok/s6.7 GB | ✓ ~97 tok/s6.7 GB | ✓ ~58 tok/s10.2 GB | ✓ ~61 tok/s10.2 GB |
| Qwen3 14B | ✓ ~55 tok/s10.6 GB | ✓ ~58 tok/s10.6 GB | ✗needs 17 GB | ✓ ~35 tok/s16.9 GB |
| Qwen3 32B | ✗needs 21 GB | ✓ ~27 tok/s21.5 GB | ✗needs 35 GB | ✗needs 35 GB |
| Qwen3 30B-A3B (MoE) | ✗needs 19 GB | ✓ ~213 tok/s19.0 GB | ✗needs 32 GB | ✗needs 32 GB |
| Qwen2.5 Coder 32B Instruct | ✗needs 21 GB | ✓ ~27 tok/s21.5 GB | ✗needs 35 GB | ✗needs 35 GB |
| Qwen3 235B-A22B (MoE) | ✗needs 135 GB | ✗needs 135 GB | ✗needs 235 GB | ✗needs 235 GB |
| Gemma 3 12B IT | ✓ ~69 tok/s8.7 GB | ✓ ~73 tok/s8.7 GB | ✓ ~41 tok/s13.9 GB | ✓ ~43 tok/s13.9 GB |
| Gemma 3 27B IT | ✗needs 18 GB | ✓ ~34 tok/s17.5 GB | ✗needs 29 GB | ✗needs 29 GB |
| Mistral 7B Instruct v0.3 | ✓ ~105 tok/s6.1 GB | ✓ ~110 tok/s6.1 GB | ✓ ~65 tok/s9.2 GB | ✓ ~68 tok/s9.2 GB |
| Mistral Small 24B Instruct (2501) | ✓ ~36 tok/s15.6 GB | ✓ ~38 tok/s15.6 GB | ✗needs 26 GB | ✗needs 26 GB |
| Mixtral 8x7B Instruct (MoE) | ✗needs 28 GB | ✗needs 28 GB | ✗needs 48 GB | ✗needs 48 GB |
| DeepSeek R1 Distill Llama 8B | ✓ ~96 tok/s6.5 GB | ✓ ~101 tok/s6.5 GB | ✓ ~59 tok/s9.9 GB | ✓ ~62 tok/s9.9 GB |
| DeepSeek R1 Distill Qwen 14B | ✓ ~54 tok/s10.8 GB | ✓ ~57 tok/s10.8 GB | ✗needs 17 GB | ✓ ~34 tok/s17.1 GB |
| DeepSeek R1 Distill Qwen 32B | ✗needs 21 GB | ✓ ~27 tok/s21.5 GB | ✗needs 35 GB | ✗needs 35 GB |
| FLUX.1 [dev] | ✓ fits9.9 GB | ✓ fits9.9 GB | ✓ fits15.0 GB | ✓ fits15.0 GB |
| FLUX.1 [schnell] | ✓ fits9.9 GB | ✓ fits9.9 GB | ✓ fits15.0 GB | ✓ fits15.0 GB |
| Stable Diffusion XL 1.0 | ✓ fits5.2 GB | ✓ fits5.2 GB | ✓ fits6.3 GB | ✓ fits6.3 GB |
| Wan 2.1 T2V 14B (video) | ✓ fits14.9 GB | ✓ fits14.9 GB | ✗needs 21 GB | ✓ fits20.9 GB |
| Wan 2.1 T2V 1.3B (video) | ✓ fits4.6 GB | ✓ fits4.6 GB | ✓ fits5.2 GB | ✓ fits5.2 GB |
8K-token context. tok/s = rough bandwidth-based estimate. Method.
FAQ
Is the RTX 5080 or RTX 4090 better for local AI?
VRAM: the RTX 4090 has 8 GB more, so it fits bigger models: at Q4 it runs Qwen3 32B, Qwen3 30B-A3B (MoE), Qwen2.5 Coder 32B Instruct, Gemma 3 27B IT, which the RTX 5080 can't. Speed: the RTX 4090 has about 5% more memory bandwidth, so expect roughly 5% faster token generation on models that fit both (estimate; prompt processing and image generation depend on compute, not shown). Price: the RTX 5080 is $1,187 cheaper today ($1,879 used vs $3,066 used); per GB of VRAM that's $117 vs $128. Renting: RTX 5080 from $0.19/hr, RTX 4090 from $0.34/hr. Try both by the hour before you buy.
Which has more VRAM, RTX 5080 or RTX 4090?
RTX 5080: 16 GB; RTX 4090: 24 GB.
Is the RTX 4090 faster than the RTX 5080 for LLMs?
For token generation, likely yes by roughly 5% (memory bandwidth 1,008 vs 960 GB/s). This is an estimate, not a benchmark.
How much do the RTX 5080 and RTX 4090 cost today?
RTX 5080: about $1,879 (used, GPU Sold). RTX 4090: about $3,066 (used, GPU Sold). Observed Nov 12, 2026.
More comparisons
Get the weekly GPU price drops
Cheapest card per model, new and used. Free, 1 email a week.
Subscribe on beehiiv →