As an Amazon Associate, SpecPicks earns from qualifying purchases.
An RTX 3060 12GB generates at a median 55.2 tok/s on 8B-class models — the midpoint of the 25 public benchmark runs collected below — on a 170 W board carrying 12 GB of GDDR6 (TechPowerUp). That pairing is the entire case for the card: 12 GB holds a 14B-parameter model at Q4 entirely in VRAM, which the 8 GB cards it sits beside on the shelf cannot do at any speed, and it does so on a single 8-pin connector. It is why a four-year-old mid-range GPU is still the default recommendation in local-LLM threads in 2026.
This page is the head of the SpecPicks RTX 3060 cluster. It collects what 49 public benchmark runs across 14 independent sources say the card actually does, where its ceiling is, and which of the deeper articles on this site answers each narrower question. If you have not chosen a card yet, the cross-card decision lives in Best GPUs for Running Local LLMs in 2026 — this page assumes the 3060 is already on your list.
What an RTX 3060 12GB actually runs
Generation speed below is the median across every published Q4 run on file for this card, with the observed range beside it so the spread is visible rather than hidden behind an average. The VRAM column is arithmetic, not a measurement: Q4_K_M weights take roughly 0.55 GB per billion parameters, and the runtime plus a usable KV cache wants about 2 GB on top of that. Everything else in the table is measured.
| Model size | Weights at Q4 | Fits in 12 GB? | Measured generation speed | What that means |
|---|---|---|---|---|
| 1-4B (Llama 3.2 3B, Qwen 3 4B) | ~2 GB | Yes | 128.3 tok/s (median of 6; 122.8-184 observed) | Fits with the whole context window to spare. Bandwidth-bound, not capacity-bound. |
| 7-9B (Llama 3.1 8B, Qwen 3 8B) | ~5 GB | Yes | 55.2 tok/s (median of 25; 11-80.6 observed) | The band this card is bought for. Weights and a long context both fit in 12 GB. |
| 12-14B (Qwen 3 14B, Phi-4, Mistral Nemo) | ~8 GB | Yes | 29.4 tok/s (median of 17; 22.7-35.8 observed) | Fits at Q4 with a moderate context. This is where an 8 GB card stops and this one does not. |
| 20-27B (Gemma 3 27B, Mistral Small) | ~15 GB | No | 5 tok/s (1 run — not a median) | Does not fit at Q4. Anything measured here is partly executing on the CPU. |
| 30-35B (Qwen 3 32B, QwQ 32B) | ~19 GB | No | No runs on file | Out of reach at usable quality. Q2 fits the weights and wrecks the output. |
The shape of that table is the whole argument for the card. Going from an 8B model to a 14B model costs roughly 47% of generation speed — a real cost, but a survivable one, because both models are still resident in VRAM. The step from 14B to 27B is not a slowdown of that kind; it is the point where the weights stop fitting and part of the model starts executing on the CPU, and the single-digit figure in the 20-27B row reflects that rather than any property of the GPU.
Sources contributing runs to this table: geerlingguy, geerlingguy/ai-benchmarks GitHub, GitHub - XiongjieDai/GPU-Benchmarks-on-LLM-Inference, GitHub Gist, Hardware-Corner, llama.cpp GitHub Discussion #10879, llmrun.dev, LocalLLaMA, and 6 others. Per-row source links are on the RTX 3060 benchmark page.
Where the 12 GB ceiling actually is
The number people quote is the model size. The number that ends the conversation is the model size plus the context window. A 14B model at Q4_K_M occupies about 8 GB of weights, which leaves roughly 3.5 GB for the KV cache once the runtime has taken its share — enough for a 16k to 32k context on most architectures, and not enough for the 128k windows the model cards advertise. Public measurements collected in How Much VRAM Does 32k Context Use on an RTX 3060 12GB? put real figures against that budget.
Below the ceiling the card behaves predictably; above it, throughput does not degrade gracefully. Once any layer spills to system RAM, generation speed is governed by PCIe and DDR bandwidth rather than the GPU's 360 GB/s, and community reports of single-digit tok/s on 27B-class models on this card are consistent with that — not with the card being slow.
How it compares to the cards people cross-shop
Every card below is measured on the same axis: median generation speed across published Q4 runs at 7-18B parameters, the band the 3060 12GB is bought for. Comparing cards at "the largest model each one fits" would put a 32B row beside a 14B row and read as a speed gap that is really a model-size gap. The set is consumer cards with an MSRP at or under $1,200; datacenter accelerators are faster and are not what anyone shopping this card is choosing between.
| GPU | VRAM | MSRP | Median tok/s at 7-18B Q4 | Runs on file |
|---|---|---|---|---|
| NVIDIA GeForce RTX 3080 | 10 GB | $699 | 98.7 | 11 |
| NVIDIA GeForce RTX 3080 Ti | 12 GB | $1,199 | 87.5 | 14 |
| NVIDIA GeForce RTX 2080 Ti | 11 GB | $999 | 85 | 7 |
| NVIDIA GeForce RTX 5080 | 16 GB | $999 | 78 | 10 |
| NVIDIA GeForce RTX 5070 Ti | 16 GB | $749 | 65.5 | 13 |
| NVIDIA GeForce RTX 2070 | 8 GB | $499 | 64.6 | 8 |
| Radeon RX 9060 XT 16GB | 16 GB | $349 | 62.3 | 6 |
| NVIDIA GeForce RTX 4080 SUPER | 16 GB | $999 | 62 | 7 |
| NVIDIA GeForce RTX 3070 | 8 GB | $499 | 61.6 | 21 |
| NVIDIA GeForce RTX 3060 12GB ← | 12 GB | $329 | 42 | 26 |
Read the VRAM column before the tok/s column. 2 of the cards above carry 8 GB and post a higher median than the 3060 — on models small enough for 8 GB, they are genuinely faster. On a 14B model none of them hold the weights, and a card that is offloading to system RAM does not have a tok/s figure worth comparing. That asymmetry, not raw throughput, is what a $329 card is being bought for.
Where the card sits right now
Last recorded at $415 in the SpecPicks catalog. Street pricing on a four-year-old card is volatile and the figure above is a snapshot, not a quote — check the live listing before committing.
🛒 Check current price on Amazon · Full specs and alternatives
Price and availability may vary. As an Amazon Associate, SpecPicks earns from qualifying purchases.
The rest of the RTX 3060 cluster
Each of the pages below answers one narrower question than this one. They are grouped by the question, not by publication date.
What fits in 12 GB
The capacity question, answered per model family.
- Gemma 4 31B Uncensored on a 12GB RTX 3060: What Fits, How Fast
- Forza Horizon 6: Is 8GB VRAM Enough or Do You Need an RTX 3060 12GB?
- Running GLM-5.2 Locally on an RTX 3060: Ollama VRAM + tok/s
- What Fits in 12GB VRAM? RTX 3060 Local LLM Model Guide (2026)
- Can a 12GB RTX 3060 Run Bonsai 27B, the New Open Reasoning Model?
- 32B Models on 12GB VRAM: What an RTX 3060 Can Really Run in 2026
- RTX 3060 12GB Local LLM Guide: Which Models Actually Fit
- Can the RTX 3060 12GB Run Qwen3-27B Locally in 2026?
Runtimes and backends
Same card, different software — the gap between these is larger than most buyers expect.
- Ollama on a 12GB RTX 3060: Best Models and tok/s in 2026
- CUDA 13.3 and the RTX 3060: What Changes for Local LLM Inference
- Intel LLM-Scaler vLLM 1.4 on Arc Pro B70: What the Latest Driver Stack Means for Local Inference
- Open WebUI + Ollama on an RTX 3060: The Self-Hosted ChatGPT Alternative for 2026
- llama.cpp vs Ollama on an RTX 3060 12GB: Which Runner Wins?
- Ollama vs llama.cpp vs vLLM on an RTX 3060 12GB: Fastest Runtime?
- llama.cpp Vulkan vs CUDA on a 12GB RTX 3060: Which Backend Wins?
Local against the frontier clouds
How close a $300 card gets to a hosted frontier model, and where it does not.
- Claude Opus 4.8 Tops the Intelligence Index — How Close Can a $300 RTX 3060 Get Locally?
- GPT-5.5 Instant Shipped: What an RTX 3060 12GB Local Stack Covers When OpenAI Retires a Model
- Claude Opus 4.8 Raised the Bar — Best Local Coding LLMs for a 12GB RTX 3060
- Claude Opus 4.8 Tops the Intelligence Index: Cloud vs Local on a 3060
- Gemini 3.6 Flash Shipped: Why Local Builders Still Reach for a 12GB GPU
- Cerebras Says It's Running GPT-5.5 Internally — What It Means for Local LLM Boxes
Against the alternatives
The other cards this one is cross-shopped against, one comparison each.
- Ryzen AI Max+ 395 128GB vs RTX 3060 12GB for Local LLMs
- Intel Arc B580 & Arc Pro B60 24GB vs RTX 3060 12GB for Local LLMs
- Reve 2.0 Debuts at #2 for Text-to-Image: Can You Run Local Image Gen on an RTX 3060?
- Ryzen AI Max 400 Gorgon Halo vs RTX 3060 for Local LLMs
- OpenAI Codex Now Drives Windows Autonomously: What It Means for Local AI Rigs
- Microsoft + Nvidia Agent PCs vs a DIY RTX 3060 12GB Local-Agent Box
- RTX 3060 12GB vs RTX 3090 for Local LLMs (2026)
- RTX 3090 vs RTX 4090 for LLM Inference: Same 24GB (2026)
- RTX 3060 12GB vs RTX 5060: Best Value for 1080p Gaming + Local AI
Running specific models
Per-model throughput and setup notes.
- Gemma 4 12B Speech-to-Text on an RTX 3060 12GB: Local Transcription tok/s
- DiffusionGemma Runs Locally: Google's Diffusion Text Model on a 12GB RTX 3060
- Best GPU for Local Llama 3 8B Under $400: Why the RTX 3060 12GB Wins
- Qwen3.6 35B on a Single RTX 3060 12GB: What Actually Fits
- Qwen3.6 35B-A3B Just Cleared FoodTruck-Bench: What the MoE Sparse Path Means for 12GB Cards
- GLM-5.2 Review: Running the Top Open-Weights LLM on an RTX 3060
- Best GPU for Running Llama 3 8B Locally Under $350 (2026)
Coding agents and tooling
What the card supports once the model is running.
- NotebookLM Now Runs Code: Self-Hosting the Same Idea on a 12GB GPU
- Benchmarking Open Models for Agentic Tool Use on an RTX 3060
- Running a Local Coding Agent on an RTX 3060 12GB: Qwen3-Coder in Practice
- Intelligence Index v4.1 Goes Agentic: Can a 12GB RTX 3060 Keep Up Locally?
- On-Device AI Keyboards: What a Sub-2GB LLM Needs to Run Local
- ComfyUI on an RTX 3060 12GB: Real Image-Gen Throughput in 2026
- Which Open LLMs Actually Handle Tool-Calling on an RTX 3060?
The cross-card decision — whether a 3060 is the right buy at all against a used 3090, an Arc B-series, or a 16 GB RDNA card — is at Best GPUs for Running Local LLMs in 2026. Hardware-tier builds around this card are on the AI Rigs hub.
Buying the card
What it costs today, and what else is in the same bracket.
Gaming on the same card
The other half of the purchase: the same 12 GB at 1080p.
- Is the RTX 3060 12GB Still Worth It for 1080p Gaming in 2026?
- Best Budget GPU for 1080p Gaming in 2026: Is the RTX 3060 12GB Still the Pick?
Citations and sources
- NVIDIA — GeForce RTX 3060 product page — board power, memory configuration, system requirements.
- TechPowerUp — GeForce RTX 3060 12 GB database entry — memory bandwidth, bus width, die specifications.
- llama.cpp — performance discussion #4167 — community throughput measurements by card and quantization.
- r/LocalLLaMA — community-reported tok/s figures aggregated into the tables above.
- Hugging Face — quantization overview — the quantization formats the VRAM arithmetic assumes.
Benchmark medians on this page are computed at render time from 49 published runs held in the SpecPicks benchmark database across 14 sources (geerlingguy, geerlingguy/ai-benchmarks GitHub, GitHub - XiongjieDai/GPU-Benchmarks-on-LLM-Inference, GitHub Gist, Hardware-Corner, llama.cpp GitHub Discussion #10879, llmrun.dev, LocalLLaMA, LocalScore.ai, PromptQuorum, singhajit.com, smeltcore.com, and 2 others); each row's source link is on the RTX 3060 benchmark page.
This piece is editorial synthesis based on publicly available information. No independent first-party benchmarking is reported.
