AMD · RDNA 2 · 8 GB VRAM tier
Best AI Models for AMD Radeon RX 6600 (8 GB)
Runs 7–9B models well; 14B doesn't fit in 8 GB.
8 GB at 224 GB/s fits ~7-8B Q4 models, no more. Not on AMD's official ROCm list; the Vulkan backend (llama.cpp, LM Studio) is the easy path.
| # | Model | Speed | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 21.1 t/s | 21.1 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 41.2 t/s | 41.2 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 22.0 t/s | 22.0 tok/s | Q4_K_M · 7.3 GB | |
| 4 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 47.3 t/s | 47.3 tok/s | Q4_K_M · 5.0 GB | |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 85.1 t/s | 85.1 tok/s | Q4_K_M · 5.5 GB |
| # | Model | Speed | Reasoning Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 21.1 t/s | 21.1 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 47.3 t/s | 47.3 tok/s | Q4_K_M · 5.0 GB | |
| 3 | Qwen2.5 7B InstructAlibaba Q4_K_M · 5.8 GB · 26.9 t/s | 26.9 tok/s | Q4_K_M · 5.8 GB | |
| 4 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 22.0 t/s | 22.0 tok/s | overall | Q4_K_M · 7.3 GB |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 85.1 t/s | 85.1 tok/s | Q4_K_M · 5.5 GB |
| # | Model | Speed | Long context Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 41.2 t/s | 41.2 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 21.1 t/s | 21.1 tok/s | Q4_K_M · 6.6 GB | |
| 3 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 25.3 t/s | 25.3 tok/s | Q4_K_M · 5.6 GB | |
| 4 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 85.1 t/s | 85.1 tok/s | Q4_K_M · 5.5 GB | |
| 5 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 70.7 t/s | 70.7 tok/s | Q4_K_M · 2.5 GB |
| # | Model | Speed ↓ | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 41.2 t/s | 41.2 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 85.1 t/s | 85.1 tok/s | Q4_K_M · 5.5 GB | |
| 3 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 70.7 t/s | 70.7 tok/s | Q4_K_M · 2.5 GB | |
| 4 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 25.3 t/s | 25.3 tok/s | Q4_K_M · 5.6 GB | |
| 5 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 21.1 t/s | 21.1 tok/s | Q4_K_M · 6.6 GB |
| # | Model | Speed | Vision Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 21.1 t/s | 21.1 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 41.2 t/s | 41.2 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 47.3 t/s | 47.3 tok/s | Q4_K_M · 5.0 GB | |
| 4 | Q4_K_M · 6.5 GB · 21.6 t/s | 21.6 tok/s | Q4_K_M · 6.5 GB | |
| 5 | MiniCPM V 4.7 1BOpenBMB Q4_K_M · 1.6 GB · 105 t/s | 105 tok/s | Q4_K_M · 1.6 GB |
The RX 6600 is an entry card in the 8 GB class: it runs 7–9B models well. It is power-hungry for its speed, and fair value at ≈$220 used. RDNA 2 generation, released 2021.
RX 6600 strengths and weaknesses
Strengths
- Runs 7–9B models: Qwen3.5 9B at 21.1 tok/s in 6.6 GB
- Low power draw: 132 W board power; a 300 W PSU is enough
Weaknesses
- 14B models don't fit: Qwen3 14B needs 11.9 GB at Q4 vs 8 GB here
- Little room for context: Qwen3.5 9B uses 6.6 of 8 GB, 1.4 GB left
- Slow prompt reading: A 4K-token prompt on Qwen3.5 9B waits 20.1 s for the first token
- ROCm, not CUDA: No FP8 weights; MXFP4 only through llama.cpp, not vLLM
Speed per dollar and per watt
On Qwen3.5 9B (9B params) at Q4_K_M. New prices are compared with new, used with used. The last two columns are the speed you get per $100 of price and per 100 W of board power; higher is better. The RX 6600 has no new price, so the New view shows it at its MSRP.
| Card | New price | tok/s | tok/s per $100 | tok/s per 100 W |
|---|---|---|---|---|
RTX 50608 GBBest new value | about $460 | 45.8 | 10.0 | 31.6 |
RTX 507012 GB | about $840 | 68.7 | 8.2 | 27.5 |
RX 66008 GB | about $329 | 21.1 | 6.4 | 16.0 |
RTX 40608 GB | about $520 | 27.8 | 5.3 | 24.2 |
| Card | Used price | tok/s | tok/s per $100 | tok/s per 100 W |
|---|---|---|---|---|
RTX 3060 12GB12 GB | about $329 | 36.8 | 11.2 | 21.6 |
RTX 50608 GBBest used value | about $430 | 45.8 | 10.7 | 31.6 |
RX 66008 GB | about $220 | 21.1 | 9.6 | 16.0 |
RTX 407012 GB | about $575 | 51.5 | 9.0 | 25.8 |
RTX 40608 GB | about $335 | 27.8 | 8.3 | 24.2 |
RTX 4070 SUPER12 GB | about $675 | 51.5 | 7.6 | 23.4 |
RTX 4060 Ti 8GB8 GB | about $400 | 29.4 | 7.4 | 18.4 |
RTX 4070 Ti12 GB | about $722 | 51.5 | 7.1 | 18.1 |
Cost per token: the RX 6600 against 8–12 GB cards
On Qwen3.5 9B (9B params, Q4_K_M, 4K context). Speed, cost per token and power per token depend on the model.
- Card, used price
- $0.66
- Power
- $0.26
Renting costs as much as buying after ≈1,000 hours (≈0.7 years at 4 h a day).
Each dot is a card; hover or tap it for its numbers, click to open it. Cards without a price for the chosen basis are left out. How we calculate cost per token
Cards people weigh against the RX 6600, each with the one reason it is worth a look. Speeds on Qwen3.5 9B.
Output speed depends on memory bandwidth (224 GB/s). Grey rows need more than 8 GB.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB21.1tok/s
- 14BQwen3 14B · not at 4-bitneeds 11.9 GB
- 27–31BQwen3.8 27B · not at 4-bitneeds 17.9 GB
- 35B MoEQwen3.6 35B A3B · not at 4-bitneeds 22.0 GB
- 70BLlama 3.3 70B Instruct · not at 4-bitneeds 51.3 GB
- 120B MoEGPT OSS 120B · not at 4-bitneeds 70.8 GB
Estimated speeds: Q4_K_M, 4K context, one user. How we estimate
All 842 models on the RX 6600
Featured onlyBest quant that fits, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works
| Model | Quant | VRAM | Speed | Context | Score | Fit |
|---|---|---|---|---|---|---|
Gemma 2 2B ITChat | Q4_K_M | 2.6 GB | 63.7 t/s | 8K | A84, Runs well | |
NVIDIA Nemotron 3 Nano 4B BF16ChatFunctions | Q4_K_M | 2.9 GB | 46.3 t/s | 262K | A78, Runs well | |
| Q4_K_M | 1.0 GB | 133.1 t/s | 2K | S95, Runs great | ||
| Q4_K_M | 7.3 GB | 24.9 t/s | 131K | B50, Decent | ||
| BF16 | 1.2 GB | 129.2 t/s | 131K | S95, Runs great | ||
Granite Docling 258MVisionChatCodeMath | Q4_K_M | 0.6 GB | 268.8 t/s | 8K | S100, Runs great | |
Zeta 2.1Chat | Q4_K_M | 7.4 GB | 24.3 t/s | 33K | B46, Decent | |
Tiny Dummy Qwen2Chat | Q4_K_M | 0.5 GB | 448.0 t/s | 33K | S100, Runs great | |
MedScholar 1.5BChat | Q4_K_M | 1.7 GB | 105.0 t/s | 33K | S92, Runs great | |
Qwen2.5 1.5B InstructChatFunctions | Q4_K_M | 1.7 GB | 105.0 t/s | 33K | S92, Runs great | |
Llama 3.2 1BChat | Q4_K_M | 1.6 GB | 121.1 t/s | 131K | S95, Runs great | |
MIST Mini 8BChat | Q4_K_M | 7.3 GB | 24.9 t/s | 131K | B50, Decent | |
Translategemma 4B ITVision | Q4_K_M | 5 GB | 47.3 t/s | — | A79, Runs well | |
Typhoon Ocr1.5 2BVisionFunctions | Q4_K_M | 3.5 GB | 74.3 t/s | 262K | S86, Runs great | |
SmolLM3 3B ONNXChat | Q4_K_M | 3.3 GB | 59.7 t/s | 66K | A84, Runs well |
Specs
- Architecture
- RDNA 2
- VRAM
- 8 GB GDDR6
- Memory bandwidth
- 224.0 GB/s
- FP16 (dense)
- 17.86 TFLOPS
- Stream processors
- 1,792
- TDP
- 132 W
- Released
- 2021-10-13
- MSRP
- $329
RX 6600 FAQ
Is the RX 6600 still worth it in 2026?
At ≈$220 used you get 9.6 tok/s per $100 on Qwen3.5 9B, which ranks 3rd of the 8 cards compared here; it is also the 19th fastest out of 19 cards with 8 GB. It runs 7–9B models well; 14B doesn't fit in 8 GB.
What is the largest model the RX 6600 can run?
Qwen3.5 9B (9.7B) is the largest at 4-bit or better: at Q4_K_M it uses 6.6 GB of 8 GB, and runs at about 21.1 tok/s.
Can the RX 6600 run 14B models?
No. Qwen3 14B needs 11.9 GB at Q4, more than the 8 GB on this card.
How many tokens per second does the RX 6600 give?
About 21.1 tok/s on Qwen3.5 9B at Q4_K_M, with the first token after 20.1 s on a 4K-token prompt.
What power supply does the RX 6600 need?
Plan a 300 W PSU (2× the 132 W TDP).
Is renting cheaper than buying an RX 6600?
An RTX 5080 (16 GB) rents from $0.22/hr. Renting costs as much as buying after ≈1,000 hours (≈0.7 years at 4 h a day).