Best AI Models for NVIDIA GeForce RTX 3060 8GB (8.0GB)
8 GB is an entry-level tier for local AI. You can run small 7B models at lower quantization levels, which is great for experimenting but comes with quality and speed trade-offs.
With 8 GB, you're limited to smaller models and lower quantization levels, but it's still enough for a meaningful local AI experience. Phi 3 Mini (3.8B) and similar compact models run well at Q4_K_M. For 7B models like Mistral 7B and Llama 3 8B, you'll need Q2_K or Q3_K_M quantization, which reduces output quality. Think of this tier as ideal for learning and experimentation rather than production workloads.
Runs Well
- 3B–4B models at Q4–Q5 quality
- 7B models at Q2–Q3 (usable but reduced quality)
- Quick experiments and learning
Challenging
- 7B models at Q4+ (VRAM too tight)
- Any model above 7B parameters
- Long context windows even with small models
What LLMs Can NVIDIA GeForce RTX 3060 8GB Run?
77 models · 13 excellent · 39 good
Showing compatibility for NVIDIA GeForce RTX 3060 8GB
| Model | Quant | VRAM | Speed | Context | Status | Grade |
|---|---|---|---|---|---|---|
Q4_K_M·28.9 t/s tok/s·262K ctx·RUNS WELL | Q4_K_M | 5.4 GB | 28.9 t/s | 262K | RUNS WELL | A69 |
Q4_K_M·31.3 t/s tok/s·131K ctx·RUNS WELL | Q4_K_M | 5.0 GB | 31.3 t/s | 131K | RUNS WELL | A71 |
Q4_K_M·30.1 t/s tok/s·RUNS WELL | Q4_K_M | 5.2 GB | 30.1 t/s | — | RUNS WELL | A71 |
Q4_K_M·30.6 t/s tok/s·33K ctx·RUNS WELL | Q4_K_M | 5.1 GB | 30.6 t/s | 33K | RUNS WELL | A71 |
Q4_K_M·31.0 t/s tok/s·262K ctx·RUNS WELL | Q4_K_M | 5.0 GB | 31.0 t/s | 262K | RUNS WELL | A71 |
Q4_K_M·30.2 t/s tok/s·33K ctx·RUNS WELL | Q4_K_M | 5.2 GB | 30.2 t/s | 33K | RUNS WELL | A71 |
Q4_K_M·32.6 t/s tok/s·66K ctx·RUNS WELL | Q4_K_M | 4.8 GB | 32.6 t/s | 66K | RUNS WELL | A72 |
Q4_K_M·39.4 t/s tok/s·33K ctx·RUNS WELL | Q4_K_M | 4.0 GB | 39.4 t/s | 33K | RUNS WELL | A75 |
Q4_K_M·33.8 t/s tok/s·4K ctx·RUNS WELL | Q4_K_M | 4.6 GB | 33.8 t/s | 4K | RUNS WELL | A73 |
Q4_K_M·45.5 t/s tok/s·131K ctx·RUNS WELL | Q4_K_M | 3.4 GB | 45.5 t/s | 131K | RUNS WELL | A77 |
Q4_K_M·31.3 t/s tok/s·4K ctx·RUNS WELL | Q4_K_M | 5.0 GB | 31.3 t/s | 4K | RUNS WELL | A71 |
Q4_K_M·43.5 t/s tok/s·RUNS WELL | Q4_K_M | 3.6 GB | 43.5 t/s | — | RUNS WELL | A77 |
Q4_K_M·45.9 t/s tok/s·4K ctx·RUNS WELL | Q4_K_M | 3.4 GB | 45.9 t/s | 4K | RUNS WELL | A78 |
Q4_K_M·33.8 t/s tok/s·8K ctx·RUNS WELL | Q4_K_M | 4.6 GB | 33.8 t/s | 8K | RUNS WELL | A73 |
Q4_K_M·38.3 t/s tok/s·4K ctx·RUNS WELL | Q4_K_M | 4.1 GB | 38.3 t/s | 4K | RUNS WELL | A75 |
Q4_K_M·53.8 t/s tok/s·41K ctx·RUNS WELL | Q4_K_M | 2.9 GB | 53.8 t/s | 41K | RUNS WELL | A81 |
NVIDIA GeForce RTX 3060 8GB Specifications
- Brand
- NVIDIA
- Architecture
- Ampere
- Compute Capability
- 8.6 (CUDA SM version)
- VRAM
- 8.0 GB GDDR6
- Memory Bandwidth
- 240.0 GB/s
- CUDA Cores
- 3,584
- Tensor Cores
- 112
- FP16 Performance
- 25.50 TFLOPS
- TDP
- 170W
- Release Date
- 2022-10-01
- MSRP
- $329
Get Started
Prompt Processing
Estimated for GLM 4 9B 0414, the compute-bound phase that reads your prompt before the first reply token appears.
Short chat
839 ms
512 tok prompt
Long chat
6.7 s
4,096 tok prompt
Document / codebase
53.7 s
32,768 tok prompt
Prefill is compute-bound and a different number from the decode tok/s shown elsewhere on this page — how prompt processing works →
Efficiency & Value
Based on GLM 4 9B 0414 at ~25.9 tok/s decode.
Tokens per watt
Higher is better.
$ per tok/s (MSRP)
MSRP-based, not street price. Lower is better.
Performance figures are estimates calibrated as of 2026-07-30 — see calibration basis →
GPUs to Consider Over NVIDIA GeForce RTX 3060 8GB
Similar GPUs and upgrades with more VRAM or higher bandwidth for AI
NVIDIA GeForce RTX 5080
NVIDIA · Blackwell
NVIDIA GeForce RTX 3080 Ti
NVIDIA · Ampere
NVIDIA GeForce RTX 5070 Ti
NVIDIA · Blackwell
NVIDIA GeForce RTX 3080
NVIDIA · Ampere
NVIDIA GeForce RTX 4080 SUPER
NVIDIA · Ada Lovelace
NVIDIA GeForce RTX 4080
NVIDIA · Ada Lovelace
Frequently Asked Questions
- Can NVIDIA GeForce RTX 3060 8GB run Qwen3 8B?
Yes, the NVIDIA GeForce RTX 3060 8GB with 8 GB can run Qwen3 8B, Gemma 4 E4B IT, Llama 3.1 8B Instruct, and 1162 other models. 400 models run at excellent quality, and 535 at good quality. Check the compatibility table above for the full list with VRAM usage and estimated speed.
- Is NVIDIA GeForce RTX 3060 8GB good for AI?
The NVIDIA GeForce RTX 3060 8GB has 8 GB of GDDR6, making it usable for running local AI models. It supports 935 models at good quality or better. With 240.0 GB/s memory bandwidth, it delivers reasonable token generation speeds. You can run smaller models and experiment with quantized 7B models.
- How many parameters can NVIDIA GeForce RTX 3060 8GB handle?
With 8 GB, the NVIDIA GeForce RTX 3060 8GB supports models from 1B to 7B parameters depending on quantization level. At Q4_K_M (the recommended sweet spot), you can fit roughly 13B parameters. Smaller 3B–7B models fit at Q3–Q4 quantization.
- What quantization should I use on NVIDIA GeForce RTX 3060 8GB?
For the best balance of quality and speed on the NVIDIA GeForce RTX 3060 8GB, start with Q4_K_M — it preserves ~85% of the original model quality while keeping VRAM usage reasonable. If a model barely fits, drop to Q3_K_M — quality loss is noticeable but still useful for chat. Avoid Q2_K unless you just want to test whether a model works at all.
- How fast is NVIDIA GeForce RTX 3060 8GB for AI inference?
With 240.0 GB/s memory bandwidth, the NVIDIA GeForce RTX 3060 8GB achieves approximately 35 tokens/sec on a 7B model at Q4_K_M — that's comfortable for real-time interactive chat. Token generation speed scales inversely with model size — smaller models are significantly faster.
tok/s = (240 GB/s ÷ model GB) × efficiency
Smaller models = faster inference. Memory bandwidth is the main bottleneck for token generation speed.
Estimated speed on NVIDIA GeForce RTX 3060 8GB
~28 tok/s~29 tok/s~29 tok/s~28 tok/sReal-world results typically within ±20%. Speed depends on quantization kernel, batch size, and software stack.
- What's the best model for NVIDIA GeForce RTX 3060 8GB?
The top-rated models for the NVIDIA GeForce RTX 3060 8GB are Qwen3 8B, Gemma 4 E4B IT, Llama 3.1 8B Instruct. The best choice depends on your use case: coding assistants benefit from code-tuned models, while general chat works well with instruction-tuned models like Llama or Qwen.
- What power supply and cooling does NVIDIA GeForce RTX 3060 8GB need?
The NVIDIA GeForce RTX 3060 8GB has a TDP of 170 W. A good rule of thumb is to provide at least double the GPU's TDP to cover the rest of the system — that means a 550 W PSU or larger. A mid-tower case with one intake and one rear exhaust is usually sufficient. Keep dust filters clean, as sustained inference generates continuous heat rather than the brief spikes typical of gaming.