NVIDIA · Blackwell · 8 GB VRAM tier
Best AI Models for NVIDIA GeForce RTX 5050 (8 GB)
Runs 7–9B models well; 14B doesn't fit in 8 GB.
Blackwell 8 GB at 320 GB/s (GDDR6, not GDDR7): ~7-8B at Q4; mid-tier decode speed with modern FP16 kernels.
| # | Model | Speed | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 32.7 t/s | 32.7 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 63.8 t/s | 63.8 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 34.1 t/s | 34.1 tok/s | Q4_K_M · 7.3 GB | |
| 4 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 73.2 t/s | 73.2 tok/s | Q4_K_M · 5.0 GB | |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 172 t/s | 172 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 · 32.7 t/s | 32.7 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 73.2 t/s | 73.2 tok/s | Q4_K_M · 5.0 GB | |
| 3 | Qwen2.5 7B InstructAlibaba Q4_K_M · 5.8 GB · 41.7 t/s | 41.7 tok/s | Q4_K_M · 5.8 GB | |
| 4 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 34.1 t/s | 34.1 tok/s | overall | Q4_K_M · 7.3 GB |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 172 t/s | 172 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 · 63.8 t/s | 63.8 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 32.7 t/s | 32.7 tok/s | Q4_K_M · 6.6 GB | |
| 3 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 39.1 t/s | 39.1 tok/s | Q4_K_M · 5.6 GB | |
| 4 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 172 t/s | 172 tok/s | Q4_K_M · 5.5 GB | |
| 5 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 70.3 t/s | 70.3 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 · 63.8 t/s | 63.8 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 172 t/s | 172 tok/s | Q4_K_M · 5.5 GB | |
| 3 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 39.1 t/s | 39.1 tok/s | Q4_K_M · 5.6 GB | |
| 4 | Q4_K_M · 6.5 GB · 33.5 t/s | 33.5 tok/s | Q4_K_M · 6.5 GB | |
| 5 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 32.7 t/s | 32.7 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 · 32.7 t/s | 32.7 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 63.8 t/s | 63.8 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 73.2 t/s | 73.2 tok/s | Q4_K_M · 5.0 GB | |
| 4 | Q4_K_M · 6.5 GB · 33.5 t/s | 33.5 tok/s | Q4_K_M · 6.5 GB | |
| 5 | LFM3 Omni 2BLiquid AI Q4_K_M · 2.4 GB · 122 t/s | 122 tok/s | Q4_K_M · 2.4 GB |
The RTX 5050 is an entry card in the 8 GB class: it runs 7–9B models well. It is more efficient per watt than most 8 GB cards, and pricier per token than most of the cards compared at ≈$410. Blackwell generation, released 2025.
RTX 5050 strengths and weaknesses
Strengths
- Runs 7–9B models: Qwen3.5 9B at 32.7 tok/s in 6.6 GB
- Low power draw: 130 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 6.7 s for the first token
- Priced well above MSRP: ≈$410 new vs its $249 MSRP (+65%)
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.
| 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 |
RTX 50508 GB | about $410 | 32.7 | 8.0 | 25.2 |
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 |
RTX 507012 GB | about $736 | 68.7 | 9.3 | 27.5 |
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 RTX 5050 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, new price
- $0.80
- Power
- $0.17
Renting costs as much as buying after ≈1,800 hours (≈1.2 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 RTX 5050, each with the one reason it is worth a look. Speeds on Qwen3.5 9B.
Output speed depends on memory bandwidth (320 GB/s). Grey rows need more than 8 GB.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB32.7tok/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 RTX 5050
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 |
|---|---|---|---|---|---|---|
| Q3_K_M | 7.8 GB | 29.7 t/s | 131K | C43, Usable | ||
GPT J 6BChat | Q4_K_M | 4.0 GB | 52.5 t/s | 2K | A81, Runs well | |
Llama 7BChat | Q4_K_M | 4.5 GB | 46.7 t/s | 2K | A78, Runs well | |
| Q4_K_M | 1.0 GB | 205.9 t/s | 2K | S100, Runs great | ||
| Q4_K_M | 6.8 GB | 42.4 t/s | 33K | A69, Runs well | ||
| Q4_K_M | 6.7 GB | 43.6 t/s | 33K | A73, Runs well | ||
| Q4_K_M | 6.2 GB | 38.6 t/s | 8K | A75, Runs well | ||
Granite 4.0 Tiny PreviewChatFunctions | Q4_K_M | 5.6 GB | 150.0 t/s | 131K | S97, Runs great | |
Starcoder2 3BChatCode | Q4_K_M | 2.6 GB | 95.4 t/s | 16K | S90, Runs great | |
| Q4_K_M | 6.0 GB | 56.4 t/s | — | A82, Runs well | ||
KernelLLMChat | Q4_K_M | 7.3 GB | 38.6 t/s | 131K | B59, Decent | |
Polyglot Ko 1.3BChat | Q4_K_M | 0.9 GB | 218.9 t/s | 2K | S100, Runs great | |
GritLM 7BChat | Q4_K_M | 6.8 GB | 42.4 t/s | 33K | A69, Runs well | |
NextCoder 7BChatCode | Q4_K_M | 5.8 GB | 41.7 t/s | 33K | A76, Runs well | |
| Q4_K_M | 6.0 GB | 56.4 t/s | — | A82, Runs well |
Specs
- Architecture
- Blackwell
- VRAM
- 8 GB GDDR6
- Memory bandwidth
- 320.0 GB/s
- FP16 (dense)
- 26.34 TFLOPS
- CUDA cores
- 2,560
- Tensor cores
- 80
- Compute capability
- 12.0
- TDP
- 130 W
- Released
- 2025-07-01
- MSRP
- $249
RTX 5050 FAQ
Is the RTX 5050 still worth it in 2026?
At ≈$410 you get 8.0 tok/s per $100 on Qwen3.5 9B, which ranks 3rd of the 4 cards compared here; it is also the 11th 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 RTX 5050 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 32.7 tok/s.
Can the RTX 5050 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 RTX 5050 give?
About 32.7 tok/s on Qwen3.5 9B at Q4_K_M, with the first token after 6.7 s on a 4K-token prompt.
What power supply does the RTX 5050 need?
Plan a 300 W PSU (2× the 130 W TDP).
Is renting cheaper than buying an RTX 5050?
An RTX 5080 (16 GB) rents from $0.23/hr. Renting costs as much as buying after ≈1,800 hours (≈1.2 years at 4 h a day).