AMD · RDNA 2 · 8 GB VRAM tier
Best AI Models for AMD Radeon RX 6650 XT (8 GB)
Runs 7–9B models well; 14B doesn't fit in 8 GB.
8 GB at 280 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 · 26.4 t/s | 26.4 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 51.5 t/s | 51.5 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 27.5 t/s | 27.5 tok/s | Q4_K_M · 7.3 GB | |
| 4 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 59.2 t/s | 59.2 tok/s | Q4_K_M · 5.0 GB | |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 96.5 t/s | 96.5 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 · 26.4 t/s | 26.4 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 59.2 t/s | 59.2 tok/s | Q4_K_M · 5.0 GB | |
| 3 | Qwen2.5 7B InstructAlibaba Q4_K_M · 5.8 GB · 33.7 t/s | 33.7 tok/s | Q4_K_M · 5.8 GB | |
| 4 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 27.5 t/s | 27.5 tok/s | overall | Q4_K_M · 7.3 GB |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 96.5 t/s | 96.5 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 · 51.5 t/s | 51.5 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 26.4 t/s | 26.4 tok/s | Q4_K_M · 6.6 GB | |
| 3 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 31.6 t/s | 31.6 tok/s | Q4_K_M · 5.6 GB | |
| 4 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 96.5 t/s | 96.5 tok/s | Q4_K_M · 5.5 GB | |
| 5 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 56.8 t/s | 56.8 tok/s | Q4_K_M · 4.3 GB |
| # | Model | Speed ↓ | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 51.5 t/s | 51.5 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 96.5 t/s | 96.5 tok/s | Q4_K_M · 5.5 GB | |
| 3 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 31.6 t/s | 31.6 tok/s | Q4_K_M · 5.6 GB | |
| 4 | Q4_K_M · 6.5 GB · 27.1 t/s | 27.1 tok/s | Q4_K_M · 6.5 GB | |
| 5 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 26.4 t/s | 26.4 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 · 26.4 t/s | 26.4 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 51.5 t/s | 51.5 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 59.2 t/s | 59.2 tok/s | Q4_K_M · 5.0 GB | |
| 4 | Q4_K_M · 6.5 GB · 27.1 t/s | 27.1 tok/s | Q4_K_M · 6.5 GB | |
| 5 | MiniCPM V 4.7 1BOpenBMB Q4_K_M · 1.6 GB · 131 t/s | 131 tok/s | Q4_K_M · 1.6 GB |
The RX 6650 XT 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 ≈$250 used. RDNA 2 generation, released 2022.
RX 6650 XT strengths and weaknesses
Strengths
- Runs 7–9B models: Qwen3.5 9B at 26.4 tok/s in 6.6 GB
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 16.7 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 6650 XT 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 6650 XT8 GB | about $399 | 26.4 | 6.6 | 14.7 |
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 6650 XT8 GB | about $250 | 26.4 | 10.6 | 14.7 |
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 6650 XT 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
- $0.60
- Power
- $0.28
Renting costs as much as buying after ≈1,100 hours (≈0.8 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 6650 XT, each with the one reason it is worth a look. Speeds on Qwen3.5 9B.
Output speed depends on memory bandwidth (280 GB/s). Grey rows need more than 8 GB.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB26.4tok/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 6650 XT
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 |
|---|---|---|---|---|---|---|
| Q4_K_M | 0.0 GB | 16800.0 t/s | 1K | S100, Runs great | ||
Qwen2.5 Omni 3BChat | Q4_K_M | 6.0 GB | 46.0 t/s | — | A78, Runs well | |
OpenMath Nemotron 1.5BChatMath | Q4_K_M | 1.7 GB | 131.3 t/s | 131K | S95, Runs great | |
Codeguard Jev Style 1.5BChatCodeFunctions | Q4_K_M | 1.7 GB | 131.3 t/s | 33K | S95, Runs great | |
| Q4_K_M | 0.3 GB | 560.0 t/s | 2K | S100, Runs great | ||
| Q4_K_M | 0.5 GB | 560.0 t/s | 33K | S100, Runs great | ||
Qwen3 Embedding 0.6BChatFunctions | Q4_K_M | 1.6 GB | 218.2 t/s | 33K | S100, Runs great | |
TwIL 8BChatReasoningMathCodeFunctions | Q4_K_S | 7.9 GB | 30.1 t/s | 131K | C41, Usable | |
| Q4_K_M | 0.5 GB | 560.0 t/s | 33K | S100, Runs great | ||
Scout 4BChatReasoningRoleplay | Q4_K_M | 3.6 GB | 51.9 t/s | 131K | A81, Runs well | |
Gemma3 1B ITChat | BF16 | 3.6 GB | 76.4 t/s | — | S87, Runs great | |
Phi 4 Mini Flash ReasoningChatMathCodeReasoning | Q4_K_M | 5.3 GB | 56.9 t/s | 262K | A82, Runs well | |
| Q4_K_M | 4.2 GB | 57.9 t/s | 41K | A83, Runs well | ||
| Q4_K_M | 0.4 GB | 560.0 t/s | 8K | S100, Runs great | ||
| BF16 | 0.2 GB | 16800.0 t/s | — | S100, Runs great |
Specs
- Architecture
- RDNA 2
- VRAM
- 8 GB GDDR6
- Memory bandwidth
- 280.0 GB/s
- FP16 (dense)
- 21.59 TFLOPS
- Stream processors
- 2,048
- TDP
- 180 W
- Released
- 2022-05-10
- MSRP
- $399
RX 6650 XT FAQ
Is the RX 6650 XT still worth it in 2026?
At ≈$250 used you get 10.6 tok/s per $100 on Qwen3.5 9B, which ranks 3rd of the 8 cards compared here; it is also the 16th fastest out of 20 cards with 8 GB. It runs 7–9B models well; 14B doesn't fit in 8 GB.
What is the largest model the RX 6650 XT 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 26.4 tok/s.
Can the RX 6650 XT 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 6650 XT give?
About 26.4 tok/s on Qwen3.5 9B at Q4_K_M, with the first token after 16.7 s on a 4K-token prompt.
What power supply does the RX 6650 XT need?
Plan a 400 W PSU (2× the 180 W TDP).
Is renting cheaper than buying an RX 6650 XT?
An RTX 5080 (16 GB) rents from $0.22/hr. Renting costs as much as buying after ≈1,100 hours (≈0.8 years at 4 h a day).