What can an RTX 4060 Ti 16GB run?
The RTX 4060 Ti 16GB has 16 GB of VRAM. The table below checks every language model in our calculator at three quantizations with an 8K-token context, using the same file sizes and fit rule as the rest of the site.
Best model for the RTX 4060 Ti 16GB: gpt-oss-20b. It is the largest model in our calculator (20.9B parameters) that fits comfortably at 4-bit: Q4_K_M plus an 8K-token FP16 KV cache needs 11.9 GB, under 90% of 16 GB. The highest precision it fits comfortably at is 16-bit (its BF16 GGUF file). In total, 11 of the 30 language models we track fit comfortably at 4-bit on this card.
| Model | 4-bit (Q4_K_M) | 8-bit (Q8_0) | 16-bit (FP16/BF16) |
|---|---|---|---|
| gpt-oss-20bOpenAI | 11.9 GB · Fits | 12.3 GB · Fits | 14.0 GB · Fits |
| Qwen2.5 14B InstructAlibaba Qwen | 10.6 GB · Fits | 17.3 GB · Too big | 31.2 GB · Too big |
| Qwen3 14BAlibaba Qwen | 10.3 GB · Fits | 17.0 GB · Too big | 30.9 GB · Too big |
| DeepSeek-R1-0528-Qwen3-8BDeepSeek | 6.2 GB · Fits | 9.9 GB · Fits | 17.6 GB · Too big |
| Llama 3.1 8B InstructMeta | 6.0 GB · Fits | 9.6 GB · Fits | 17.1 GB · Too big |
| Nemotron 3.5 Bolt E4B*NVIDIA | 6.2 GB · Fits | 8.2 GB · Fits | 15.1 GB · Tight |
| Qwen2.5 7B InstructAlibaba Qwen | 5.2 GB · Fits | 8.6 GB · Fits | 15.7 GB · Tight |
| Mistral 7B Instruct v0.3Mistral AI | 5.4 GB · Fits | 8.8 GB · Fits | 15.6 GB · Tight |
| Spark-X2.6 4BXHToken | 3.8 GB · Fits | 4.7 GB · Fits | 8.5 GB · Fits |
| Llama 3.2 3B InstructMeta | 3.0 GB · Fits | 4.4 GB · Fits | 7.4 GB · Fits |
| LFM3 1.7BLiquid AI | 1.2 GB · Fits | 1.9 GB · Fits | 3.6 GB · Fits |
| LFM2.5-24B-A2BLiquid AI | 14.7 GB · Tight | 25.7 GB · Too big | 48.1 GB · Too big |
| Kimi K3Moonshot AI | 1,508.9 GB · Too big | 1,561.4 GB · Too big | n/a |
| Mistral Large 4 (Le Chonk)Mistral AI | 635.5 GB · Too big | 1,115.8 GB · Too big | 2,099.5 GB · Too big |
| DeepSeek-V4.1-Flash-1017DeepSeek | 500.7 GB · Too big | 508.4 GB · Too big | n/a |
| Qwen3.8 Flash NextAlibaba Qwen | 119.8 GB · Too big | 188.5 GB · Too big | 354.2 GB · Too big |
| Ornith-1.5-122BOrnith | 79.9 GB · Too big | 132.8 GB · Too big | 249.6 GB · Too big |
| gpt-oss-120bOpenAI | 63.1 GB · Too big | 63.7 GB · Too big | 65.7 GB · Too big |
| Llama 3.1 70B InstructMeta | 45.2 GB · Too big | 77.7 GB · Too big | 143.8 GB · Too big |
| Llama 3.3 70B InstructMeta | 45.2 GB · Too big | 77.7 GB · Too big | 143.8 GB · Too big |
| Mixtral 8x7B Instruct v0.1Mistral AI | 27.5 GB · Too big | 50.7 GB · Too big | 94.5 GB · Too big |
| Recursive FlintRecursive | 25.3 GB · Too big | 42.5 GB · Too big | 79.8 GB · Too big |
| Qwen3.6 35B-A3BAlibaba Qwen | 22.5 GB · Too big | 38.0 GB · Too big | 71.2 GB · Too big |
| Qwen3.8-35B-A3B (Empero Distill)Empero | 21.9 GB · Too big | 38.0 GB · Too big | 71.2 GB · Too big |
| Nanbeige4.3 33BNanbeige | 22.5 GB · Too big | 36.9 GB · Too big | 68.0 GB · Too big |
| Qwen2.5 32B InstructAlibaba Qwen | 22.0 GB · Too big | 37.0 GB · Too big | 67.7 GB · Too big |
| Qwen3 32BAlibaba Qwen | 21.9 GB · Too big | 37.0 GB · Too big | 67.7 GB · Too big |
| Gemma 4 31B*Google | 19.6 GB · Too big | 32.6 GB · Too big | 61.4 GB · Too big |
| Qwen3.8 27BAlibaba Qwen | 18.0 GB · Too big | 29.7 GB · Too big | 55.2 GB · Too big |
| Gemma 4 26B A4B*Google | 17.0 GB · Too big | 26.9 GB · Too big | 50.5 GB · Too big |
Each cell is the Hugging Face GGUF file size plus FP16 KV cache for an 8K-token context (or the model's maximum, if shorter). Fits = under 90% of 16 GB; Tight = 90 to 100%; Too big = over 16 GB. * = KV cache not included (no config data). Same data as the VRAM calculator and what can I run with 16 GB. Data checked 2026-10-30.
More for 16 GB cards
- Everything that fits in 16 GB, including image generation and gaming
- Best GPUs for local LLMs: 16 GB, with specs from NVIDIA and AMD
- Run a MoE model bigger than your VRAM with expert offload to system RAM
- VRAM calculator for other context lengths
Rent a GPU
- Rent on Vast.ai Affiliate partner
- Rent on Runpod Referral
Hourly prices for the same GPU on both are on the GPU cost per hour page.
Some links on this page are affiliate or referral links: we may get a commission or account credit if you sign up. See our disclosure.
Too big for your card? Rent the VRAM by the hour, or upgrade.
Run it on a cloud GPU
No upgrade needed
Rent a 24–80 GB GPU for the hour you need it.
Vast.ai 
Runpod 
E2E Networks Buy this GPU
Own the VRAM
Compare current GPU prices first on our GPU price table and measured speeds.
We may earn from links marked Affiliate partner. Disclosure.