NVIDIA · Ada Lovelace · 12 GB VRAM tier
Best AI Models for NVIDIA GeForce RTX 4070 (12 GB)
Runs 7–9B models well; 14B only just fits.
| # | Model | Speed | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 51.5 t/s | 51.5 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 101 t/s | 101 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 3 12B ITGoogle Q4_K_M · 10.9 GB · 40.7 t/s | 40.7 tok/s | Q4_K_M · 10.9 GB | |
| 4 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 53.7 t/s | 53.7 tok/s | Q4_K_M · 7.3 GB | |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 240 t/s | 240 tok/s | Q4_K_M · 5.5 GB |
| # | Model | Speed | Coding Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Q4_K_M · 7.9 GB · 61.8 t/s | 61.8 tok/s | Q4_K_M · 7.9 GB | |
| 2 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 51.5 t/s | 51.5 tok/s | overall | Q4_K_M · 6.6 GB |
| 3 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 101 t/s | 101 tok/s | overall | Q4_K_M · 3.4 GB |
| 4 | Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 39.8 t/s | 39.8 tok/s | Q4_K_M · 9.0 GB | |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 240 t/s | 240 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 · 51.5 t/s | 51.5 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3 8BAlibaba Q4_K_M · 7.6 GB · 59.3 t/s | 59.3 tok/s | Q4_K_M · 7.6 GB | |
| 3 | Q4_K_M · 7.9 GB · 61.8 t/s | 61.8 tok/s | Q4_K_M · 7.9 GB | |
| 4 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 115 t/s | 115 tok/s | Q4_K_M · 5.0 GB | |
| 5 | Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 39.8 t/s | 39.8 tok/s | Q4_K_M · 9.0 GB |
| # | Model | Speed | Long context Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 51.5 t/s | 51.5 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 101 t/s | 101 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Q4_K_M · 7.9 GB · 61.8 t/s | 61.8 tok/s | Q4_K_M · 7.9 GB | |
| 4 | Mistral Nemo Instruct 2407Mistral AI Q4_K_M · 11.0 GB · 40.6 t/s | 40.6 tok/s | Q4_K_M · 11.0 GB | |
| 5 | Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 39.8 t/s | 39.8 tok/s | Q4_K_M · 9.0 GB |
| # | Model | Speed ↓ | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 101 t/s | 101 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 240 t/s | 240 tok/s | Q4_K_M · 5.5 GB | |
| 3 | Qwen3 8BAlibaba Q4_K_M · 7.6 GB · 59.3 t/s | 59.3 tok/s | Q4_K_M · 7.6 GB | |
| 4 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 51.5 t/s | 51.5 tok/s | Q4_K_M · 6.6 GB | |
| 5 | Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 39.8 t/s | 39.8 tok/s | Q4_K_M · 9.0 GB |
| # | Model | Speed | Vision Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 51.5 t/s | 51.5 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 101 t/s | 101 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 3 12B ITGoogle Q4_K_M · 10.9 GB · 40.7 t/s | 40.7 tok/s | Q4_K_M · 10.9 GB | |
| 4 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 115 t/s | 115 tok/s | Q4_K_M · 5.0 GB | |
| 5 | Q4_K_M · 6.5 GB · 52.8 t/s | 52.8 tok/s | Q4_K_M · 6.5 GB |
The RTX 4070 is a solid mid-range card in the 12 GB class: it runs 7–9B models well. It is more efficient per watt than most 12 GB cards, and pricier per token than most of the cards compared at ≈$575 used. Ada Lovelace generation, released 2023.
RTX 4070 strengths and weaknesses
Strengths
- Runs 14B models: Qwen3 14B at 34.5 tok/s in 11.9 GB
Weaknesses
- 27–31B models don't fit: Qwen3.8 27B needs 17.9 GB at Q4 vs 12 GB here
- Little room for context: Qwen3 14B uses 11.9 of 12 GB, 0.1 GB left
- Used prices still near MSRP: ≈$575 used vs its $599 MSRP
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 RTX 4070 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 407012 GB | about $599 | 51.5 | 8.6 | 25.8 |
RTX 507012 GB | about $840 | 68.7 | 8.2 | 27.5 |
RX 7900 XTX24 GB | about $1,130 | 90.6 | 8.0 | 25.5 |
RX 907016 GB | about $800 | 60.4 | 7.6 | 27.5 |
RX 9070 XT16 GB | about $815 | 60.4 | 7.4 | 19.9 |
RTX 40608 GB | about $520 | 27.8 | 5.3 | 24.2 |
RX 9060 XT 16GB16 GB | about $590 | 30.2 | 5.1 | 18.9 |
| Card | Used price | tok/s | tok/s per $100 | tok/s per 100 W |
|---|---|---|---|---|
RTX 50608 GBBest used value | about $388 | 45.8 | 11.8 | 31.6 |
RTX 3060 12GB12 GB | about $329 | 36.8 | 11.2 | 21.6 |
RTX 507012 GB | about $736 | 68.7 | 9.3 | 27.5 |
RX 907016 GB | about $650 | 60.4 | 9.3 | 27.5 |
RX 7900 XTX24 GB | about $1,000 | 90.6 | 9.1 | 25.5 |
RTX 407012 GB | about $575 | 51.5 | 9.0 | 25.8 |
RTX 4070 SUPER12 GB | about $675 | 51.5 | 7.6 | 23.4 |
RX 9060 XT 16GB16 GB | about $480 | 30.2 | 6.3 | 18.9 |
Cost per token: the RTX 4070 against 8–24 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
- $0.71
- Power
- $0.16
Renting costs as much as buying after ≈4,200 hours (≈2.9 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 4070, each with the one reason it is worth a look. Speeds on Qwen3.5 9B.
Output speed depends on memory bandwidth (504 GB/s). Grey rows need more than 12 GB.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB51.5tok/s
- 34.5tok/s
- 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 956 models on the RTX 4070
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 | 1.7 GB | 255.9 t/s | 33K | S100, Runs great | ||
| BF16 | 1.6 GB | 537.0 t/s | — | S100, Runs great | ||
Devstral Small 2 24B Instruct 2512ChatFunctions | IQ2_M | 11.8 GB | 37.1 t/s | 393K | C44, Usable | |
Qwen2.5 0.5BChatFunctions | Q4_K_M | 0.8 GB | 528.4 t/s | 33K | S100, Runs great | |
Yi 9BChat | Q4_K_M | 6 GB | 56.5 t/s | 4K | A82, Runs well | |
| BF16 | 7.6 GB | 57.0 t/s | — | A82, Runs well | ||
| Q4_K_M | 4.6 GB | 182.0 t/s | 33K | S99, Runs great | ||
Llama 3.2 1BChat | Q4_K_M | 2.3 GB | 399.5 t/s | — | S100, Runs great | |
BioMistral 7BChat | Q4_K_M | 6.7 GB | 68.7 t/s | 33K | S85, Runs great | |
CodeQwen1.5 7BChatCode | Q4_K_M | 5.7 GB | 68.5 t/s | 66K | S85, Runs great | |
Qwen2.5 1.5BChatFunctions | Q4_K_M | 1.7 GB | 255.9 t/s | 131K | S100, Runs great | |
| Q4_K_M | 5.0 GB | 70.9 t/s | 4K | S86, Runs great | ||
Xgen 7B 8k BaseChat | Q4_K_M | 5.7 GB | 70.9 t/s | 8K | S86, Runs great | |
Shieldgemma 2BChat | Q4_K_M | 3.6 GB | 189.4 t/s | — | S99, Runs great | |
SmolLM 360MChat | Q4_K_M | 0.6 GB | 546.0 t/s | 2K | S100, Runs great |
Specs
- Architecture
- Ada Lovelace
- VRAM
- 12 GB GDDR6X
- Memory bandwidth
- 504.0 GB/s
- FP16 (dense)
- 58.30 TFLOPS
- CUDA cores
- 5,888
- Tensor cores
- 184
- Compute capability
- 8.9
- TDP
- 200 W
- Released
- 2023-04-13
- MSRP
- $599
RTX 4070 FAQ
Is the RTX 4070 still worth it in 2026?
At ≈$575 used you get 9.0 tok/s per $100 on Qwen3.5 9B, which ranks 6th of the 8 cards compared here; it is also the 3rd fastest out of 9 cards with 12 GB. It runs 7–9B models well; 14B only just fits.
What is the largest model the RTX 4070 can run?
GPT OSS 20B (20.9B) is the largest at 4-bit or better: at IQ4_XS it uses 11.8 GB of 12 GB, and runs at about 119 tok/s.
Can the RTX 4070 run Qwen3.5 9B?
Yes. Qwen3.5 9B fits at Q4_K_M, using 6.6 GB of 12 GB, and it is the best model that runs well on this card.
Can the RTX 4070 run 27–31B models?
No. Qwen3.8 27B needs 17.9 GB at Q4, more than the 12 GB on this card.
How many tokens per second does the RTX 4070 give?
About 51.5 tok/s on Qwen3.5 9B at Q4_K_M, with the first token after 3.0 s on a 4K-token prompt.
What power supply does the RTX 4070 need?
Plan a 400 W PSU (2× the 200 W TDP).
Is 12 GB enough for coding and agents?
Yes for coding: Llama 3.1 8B Instruct, the only coding-scored model that fits, runs at about 62 tok/s. For agents, not yet: no agent-scored model fits in less than 96 GB.
Is renting cheaper than buying an RTX 4070?
Rent from $0.14/hr. Renting costs as much as buying after ≈4,200 hours (≈2.9 years at 4 h a day).