Ranking updated on 09/10/2026
The RTX 5080 (16 GB GDDR7, 960 GB/s) is the tier 2 Blackwell model. The same VRAM as the 4080, but GDDR7 + an upgraded Neural Engine = 25–30% faster on the same models.
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Dense 14B with hybrid thinking. Equals Qwen 2.5 32B Based on STEM/code.
ollama run qwen3:14b
MIT 14B reasoner. Beats R1-Distill-Llama-70B on AIME/GPQA with 50× fewer parameters.
ollama run phi4-reasoning:14b
Exceptional reasoning for its size. STEM-focused.
ollama run phi4:14b
Coding 14B. HumanEval 89.6, LiveCodeBench 37.1. VRAM sweet spot for self-hosted coding.
ollama run qwen2.5-coder:14b
Distilled R1 Qwen 14B. AIME24 69.7, MATH-500 93.9. Outperforms o1-mini on many benchmarks.
ollama run deepseek-r1:14b
Dense 14B Apache 2.0. MMLU 79.7, HumanEval 83.5. 29+ languages. Good compromise.
ollama run qwen2.5:14b
24B coding specialist, Apache 2.0. 72.2% SWE-Bench. 256k ctx, FR lab.
ollama run devstral-small2:24b
| Rank | Model | Params | Q4 VRAM | Context | License | On RTX 5080 |
|---|---|---|---|---|---|---|
| #1 | Qwen 3 14B | 14B | 9 GB | 131 072 | Apache 2.0 | 55 tok/s · Q8 |
| #2 | Phi-4 Reasoning 14B | 14B | 9 GB | 32 768 | MIT | 55 tok/s · Q8 |
| #3 | Phi-4 14B | 14B | 9 GB | 16 384 | MIT | 55 tok/s · Q8 |
| #4 | Qwen 2.5 Coder 14B Instruct | 14B | 9 GB | 131 072 | Apache 2.0 | 55 tok/s · Q8 |
| #5 | DeepSeek R1 Distill Qwen 14B | 14B | 9 GB | 131 072 | MIT | 55 tok/s · Q8 |
| #6 | Qwen 2.5 14B Instruct | 14B | 9 GB | 131 072 | Apache 2.0 | 55 tok/s · Q8 |
| #7 | Devstral Small 2 24B | 24B | 14 GB | 256 000 | Apache 2.0 | 40 tok/s · Q4_K_M |
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Get the memo VRAM → best coding model → Ollama command (one screen, copy and paste). Then switch to the Copilote Local kit for a setup that actually works.
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Your card → the best coding model to run locally, and the exact Ollama command:
| Your VRAM | Typical GPUs / Macs | Recommended coding model | Command Ollama |
|---|---|---|---|
| 8 GB | RTX 4060 / 3060 · M1-M2 16 GB | Qwen 3.5 9B (Q4, 6.6 GB — 256k context) | ollama run qwen3.5:9b |
| 12 GB | RTX 3060 12 GB / 4070 / 5070 | Qwen 3.5 9B (Q8, 11 GB) or Gemma 4 12B (7.6 GB) | ollama run qwen3.5:9b-q8_0 |
| 16 GB | RTX 5070 Ti / 4080 / 5080 · RX 9070 XT · M4 24 GB | Devstral 24B (Q4, 14 GB) — coding-agent specialist | ollama run devstral:24b |
| 24 GB | RTX 3090 / 4090 · RX 7900 XTX · M4 Pro 48 GB | Qwen 3.8 27B (Q4, 18 GB) — the “close to Copilot” option | ollama run qwen3.8:27b |
| 32 GB | RTX 5090 | Qwen 3.6 35B-A3B (Q4, 23 GB) — fast MoE | ollama run qwen3.6:35b |
| 48 GB+ | Mac M4 Max 64 GB · M2 Ultra 128 GB | Qwen3-Coder 30B-A3B (Q8, 32 GB — 256k context) | ollama run qwen3-coder:30b-a3b-q8_0 |
-base : ollama run qwen2.5-coder:7b-base — it’s still the reference for this specific use case. ⚠️ Qwen 3.8: its reasoning is set very high by default and it “overthinks” simple requests — lower it to low (or turn it off) on first launch. ⚠️ License trap: Codestral 22B = Mistral Non-Production License → prohibited for coding at work. Qwen 3.5/3.8, Gemma 4, and Devstral are Apache 2.0. 💡 Running out of memory? Keep ~1.5 GB of VRAM free for context, or drop down one quantization level.🔌 To connect it to VS Code: Cline (multi-file agent), Aider (CLI) or Tabby/Twinny (FIM autocomplete) — they all connect to Ollama locally. The kit Local Copilot — ready-to-paste configs + tested setup — is available: /copilote-local.
Filter: models whose Q4_K_M fits under 14 GB. Bonus: 7–14B (peak 5080) and 13–24B at the limit. GDDR7 bandwidth of 960 GB/s = ~30% gain vs 4080.
Criteria considered:
The scoring is fully transparent: see our methodology for details on VRAM/tokens/sec calculations.
RTX 5080 vs. RTX 4080?
Same 16 GB of VRAM. The 5080 is 25–30% faster on the same models thanks to GDDR7 (960 vs 736 GB/s) + the Blackwell Neural Engine. Mistral Small 24B Q4: 5080 ~38 tok/s vs 4080 ~28 tok/s. See RTX 4080.
Can you run 30B on a 5080?
Mistral Small 24B Q4 (~13 GB) works at 35-40 tok/s. Qwen 3 32B Q3_K_M (~14 GB) is borderline, with degraded quality. For 30-32B in comfortable Q4, target RTX 5090 32 GB. See RTX 5090.
Which quantization on 5080?
Q5_K_M for 7–9B (maximum quality, ~7 GB). Q4_K_M for 13–24B (Mistral Small 24B). Q6_K for 13–14B (Qwen 3 14B ~12 GB) is ideal.
RTX 5080 or Mac Studio M4 Max 64 GB?
M4 Max Studio = silence + 64 GB (smooth 70B Q4). 5080 = pure speed on 7-24B (35-50 tok/s). If you want 70B locally, Mac Studio. For speed on 7-24B, RTX 5080. See Mac Studio.
Learn more with our detailed head-to-head matchups of the finalists: