🇨🇳 Qwen 3 14B
Dense 14B with hybrid thinking. Equals Qwen 2.5 32B Based on STEM/code.
ollama run qwen3:14b
Ranking updated on 09/10/2026
The Radeon RX 9060 XT (16 GB GDDR6, 322 GB/s) is the entry-level RDNA 4 (2025). One of the least expensive 16 GB cards (current prices) = Mistral Small 24B Q4 accessible via ROCm 6.
Radeon RX 9060 XT 16GB: purchasing alternative available for local AI — Radeon RX 9070 XT 16 GB:
Why this choice? Our complete guide to Radeon RX 9070 XT 16 GB →
Which PC should you choose for your budget? Our picks from €800 to €3,500 →
Affiliate links — BestLLMfor may earn a commission on purchases, at no extra cost to you, which does not influence the ranking (established independently). As an Amazon Associate, BestLLMfor earns from qualifying purchases.
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
Dense 8B Apache 2.0, 12 languages including FR, 131k context, GQA 32Q/8KV. MMLU 73.84, HumanEval 85.37. Released April 29, 2026.
# HuggingFace : ibm-granite/granite-4.1-8b
| Rank | Model | Params | Q4 VRAM | Context | License | On Radeon RX 9060 XT 16GB |
|---|---|---|---|---|---|---|
| #1 | Qwen 3 14B | 14B | 9 GB | 131 072 | Apache 2.0 | 6 tok/s · Q8 |
| #2 | Phi-4 Reasoning 14B | 14B | 9 GB | 32 768 | MIT | 6 tok/s · Q8 |
| #3 | Phi-4 14B | 14B | 9 GB | 16 384 | MIT | 6 tok/s · Q8 |
| #4 | Qwen 2.5 Coder 14B Instruct | 14B | 9 GB | 131 072 | Apache 2.0 | 6 tok/s · Q8 |
| #5 | DeepSeek R1 Distill Qwen 14B | 14B | 9 GB | 131 072 | MIT | 6 tok/s · Q8 |
| #6 | Qwen 2.5 14B Instruct | 14B | 9 GB | 131 072 | Apache 2.0 | 6 tok/s · Q8 |
| #7 | Granite 4.1 8B Instruct | 8B | 5 GB | 131 072 | Apache 2.0 | 12 tok/s · FP16 |
Your private, free ChatGPT on your machine in 1 hour — LM Studio, Ollama, Open WebUI, your documents, no cloud.
Free memo
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.
The Local Copilot kit — the Ollama + Cline + Aider configs are ready to paste, with tuned Modelfiles, troubleshooting, and lifetime online access →No spam. Unsubscribe in 1 click. Your data stays with us (never resold).
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: Q4_K_M ≤ 14 GB. Bonus for 7–14B and 13–24B. 322 GB/s + ROCm 6 + RDNA 4.
Criteria considered:
The scoring is fully transparent: see our methodology for details on VRAM/tokens/sec calculations.
RX 9060 XT vs. 5060 Ti 16 GB?
9060 XT = 16 GB + 322 GB/s ROCm. 5060 Ti 16 = 16 GB + 448 GB/s CUDA, about 40% faster. NVIDIA has better support (CUDA, Ollama is more mature). Price difference: see price tracking. See RTX 5060 Ti 16GB.
Speed on 9060 XT?
Mistral 7B Q4 at around 45 tok/s, Mistral Small 24B Q4 at 16 tok/s. Acceptable for personal chat/RAG use.
9060 XT LLM sweet spot?
Mistral Small 24B Q4 (~13 GB) at 16 tok/s, Qwen 3 14B Q5 (~10 GB) at 22 tok/s.
9060 XT or 9070 (non-XT)?
9070 = 644 GB/s vs 9060 XT 322 GB/s = twice the bandwidth, so approximately twice as fast. Price difference: see price tracking. See RX 9070.
Learn more with our detailed head-to-head matchups of the finalists:
Prices in euros (€) are French market prices including VAT, as checked by BestLLMfor. US prices differ: the Amazon buttons show the current US price.