NVIDIA · Ampere · 8 GB VRAM tier
Best AI Models for NVIDIA GeForce RTX 3070 Ti Laptop GPU (8 GB)
Runs 7–9B models well; 14B doesn't fit in 8 GB.
8 GB GDDR6448 GB/s35 TFLOPS FP16125 WAmpere 2022
8 GB GDDR6 on a 256-bit bus (448 GB/s); VRAM, not compute, is the limit - ~7-8B Q4 models. Real speed depends on the chassis power limit.
| # | Model | Speed | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 45.8 t/s | 45.8 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 89.3 t/s | 89.3 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 47.7 t/s | 47.7 tok/s | Q4_K_M · 7.3 GB | |
| 4 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 103 t/s | 103 tok/s | Q4_K_M · 5.0 GB | |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 221 t/s | 221 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 · 45.8 t/s | 45.8 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 103 t/s | 103 tok/s | Q4_K_M · 5.0 GB | |
| 3 | Qwen2.5 7B InstructAlibaba Q4_K_M · 5.8 GB · 58.4 t/s | 58.4 tok/s | Q4_K_M · 5.8 GB | |
| 4 | Gemma 2 9B ITGoogle Q4_K_M · 7.3 GB · 47.7 t/s | 47.7 tok/s | overall | Q4_K_M · 7.3 GB |
| 5 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 221 t/s | 221 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 · 89.3 t/s | 89.3 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 45.8 t/s | 45.8 tok/s | Q4_K_M · 6.6 GB | |
| 3 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 54.7 t/s | 54.7 tok/s | Q4_K_M · 5.6 GB | |
| 4 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 221 t/s | 221 tok/s | Q4_K_M · 5.5 GB | |
| 5 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 98.4 t/s | 98.4 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 · 89.3 t/s | 89.3 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 221 t/s | 221 tok/s | Q4_K_M · 5.5 GB | |
| 3 | Gemma 4 E4B ITGoogle Q4_K_M · 5.6 GB · 54.7 t/s | 54.7 tok/s | Q4_K_M · 5.6 GB | |
| 4 | Q4_K_M · 6.5 GB · 46.9 t/s | 46.9 tok/s | Q4_K_M · 6.5 GB | |
| 5 | Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 45.8 t/s | 45.8 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 · 45.8 t/s | 45.8 tok/s | Q4_K_M · 6.6 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 89.3 t/s | 89.3 tok/s | Q4_K_M · 3.4 GB | |
| 3 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 103 t/s | 103 tok/s | Q4_K_M · 5.0 GB | |
| 4 | Q4_K_M · 6.5 GB · 46.9 t/s | 46.9 tok/s | Q4_K_M · 6.5 GB | |
| 5 | LFM3 Omni 2BLiquid AI Q4_K_M · 2.4 GB · 171 t/s | 171 tok/s | Q4_K_M · 2.4 GB |
See all 218 models on the RTX 3070 Ti Laptop GPU →Best quant that fits · speeds estimated on this card
The RTX 3070 Ti Laptop GPU runs 7–9B models well. Ampere generation, released 2022.
GenerationAmperereleased 2022
RTX 3070 Ti Laptop GPU strengths and weaknesses
Strengths
- Runs 7–9B models: Qwen3.5 9B at 45.8 tok/s in 6.6 GB
- Low power draw: 125 W board power; a 250 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 5.0 s for the first token
- No FP8 or NVFP4: Ampere predates both; use GGUF, AWQ or GPTQ builds
Cards people weigh against the RTX 3070 Ti Laptop GPU, each with the one reason it is worth a look.
About as fast, same 8 GBRTX 3070 TiNVIDIA · 8 GB · Ampere
same 8 GBabout $599rent $0.13/hr62.2 tok/s
8 GB more for bigger modelsRTX 4080NVIDIA · 16 GB · Ada Lovelace▲ 8 GBabout $1,199rent $0.24/hr73.3 tok/s
8 GB more for bigger modelsRTX 4080 SUPERNVIDIA · 16 GB · Ada Lovelace▲ 8 GBabout $999rent $0.26/hr75.2 tok/s
2 GB more for bigger modelsRTX 3080NVIDIA · 10 GB · Ampere▲ 2 GBabout $699rent $0.11/hr77.7 tok/s
8 GB more for bigger modelsRTX 5080 Laptop GPUNVIDIA · 16 GB · Blackwell▲ 8 GB91.6 tok/s
Best value near the RTX 3070 Ti Laptop GPURTX 5070 TiNVIDIA · 16 GB · Blackwell▲ 8 GBabout $1,170rent $0.16/hr91.6 tok/s
Output speed depends on memory bandwidth (448 GB/s). Grey rows need more than 8 GB.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB45.8tok/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 3070 Ti Laptop GPU
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 |
|---|---|---|---|---|---|---|
Tiny MixtralChat | Q4_K_M | 0.5 GB | 1206.9 t/s | 131K | S100, Runs great | |
| BF16 | 3 GB | 97.1 t/s | 2K | S91, Runs great | ||
LFM2 VL 1.6BVision | Q4_K_M | 1.5 GB | 220.6 t/s | 128K | S100, Runs great | |
Gemma 3 1B ITChat | Q4_K_M | 2.1 GB | 441.2 t/s | 33K | S100, Runs great | |
| Q4_K_M | 7.7 GB | 56.4 t/s | 33K | B58, Decent | ||
| Q4_K_M | 6.0 GB | 48.2 t/s | 131K | A79, Runs well | ||
Supra 50M BaseChat | Q4_K_M | 0.3 GB | 808.9 t/s | 1K | S100, Runs great | |
Olmo 3 7B ThinkChat | IQ4_XS | 8.0 GB | 54.9 t/s | 66K | C44, Usable | |
Distilgpt2Chat | Q4_K_M | 0.1 GB | 4853.3 t/s | 1K | S100, Runs great | |
Granite 3.3 2B InstructChatFunctions | Q4_K_M | 3.2 GB | 146.3 t/s | 131K | S97, Runs great | |
Gpt2 LargeChat | Q4_K_M | 0.5 GB | 539.3 t/s | 1K | S100, Runs great | |
| BF16 | 7.1 GB | 46.3 t/s | 8K | A66, Runs well | ||
Gemma 4 12B IT AEON Abliterated K4 BF16ChatReasoningFunctions | Q3_K_M | 7.7 GB | 42.3 t/s | 262K | B51, Decent | |
Qwen3 Code Reasoning 4BChatCodeReasoning | Q4_K_M | 4.2 GB | 100.8 t/s | 262K | S92, Runs great | |
OLMo 1B HFChat | Q4_K_M | 1.3 GB | 229.3 t/s | 2K | S100, Runs great |
Specs
- Architecture
- Ampere
- VRAM
- 8 GB GDDR6
- Memory bandwidth
- 448.0 GB/s
- FP16 (dense)
- 34.97 TFLOPS
- CUDA cores
- 5,888
- Tensor cores
- 184
- Compute capability
- 8.6
- TDP
- 125 W
- Released
- 2022-02-01
RTX 3070 Ti Laptop GPU FAQ
What is the largest model the RTX 3070 Ti Laptop GPU 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 45.8 tok/s.
Can the RTX 3070 Ti Laptop GPU 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 3070 Ti Laptop GPU give?
About 45.8 tok/s on Qwen3.5 9B at Q4_K_M, with the first token after 5.0 s on a 4K-token prompt.
What power supply does the RTX 3070 Ti Laptop GPU need?
Plan a 250 W PSU (2× the 125 W TDP).
Is renting cheaper than buying an RTX 3070 Ti Laptop GPU?
An RTX 3090 (24 GB) rents from $0.18/hr. With regular daily use, owning pays off.