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NVIDIA
Operating mode
Use this to bias workload recommendations toward responsiveness, background autonomy, lighter serving, or multi-GPU scale-out.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
The Tesla P40 is a Pascal-generation datacenter GPU from 2016, built for inference workloads before the era of large language models. At 24 GB of GDDR5X, it was notable as one of the first high-VRAM inference accelerators, and it saw renewed interest from the LLM community when NVLink 3090-class cards were scarce. It can run 7B models at Q4 quantization but generation will be slow by current standards. Available on the used market for very low prices, it remains a viable ultra-budget option for hobbyists building an inference server, though modern alternatives are strongly preferred.
Beyond LLMs
What AI tasks this GPU can handle — from text generation to image and video creation.
| Capability | Status | Representative Model | Detail |
|---|---|---|---|
| LLM Chat (7B) | Runs natively | Llama 3.1 8B Q4 | — |
| LLM Coding (30B) | Runs natively | Qwen 3 30B Q4 | — |
| LLM Large (70B) | Won’t fit | Llama 3.1 70B Q4 | — |
| Image Gen (SDXL) | Runs natively | SDXL 1.0 FP16 | ~~17.6s per image |
| Image Gen (Flux) | Runs with offload | Flux.1 Dev FP16 | ~~1m 19s per image |
| Image Gen (SD 3.5) | Runs natively | SD 3.5 Large FP16 | ~~1m 37s per image |
| Video Short (25f) | Runs natively | LTX Video 2B | ~~15.3s/frame |
| Video Long (100f) | Won't fit | Wan Video 14B | ~~45s/frame |
Architecture
Pascal is NVIDIA's first 16nm FinFET GPU architecture, powering the GTX 10-series consumer cards and Tesla P100/P40 datacenter accelerators. It introduced unified memory architecture and NVLink interconnect for datacenter GPUs.
AI Relevance
No dedicated Tensor Cores — all AI inference runs on standard CUDA cores at FP16 or FP32 precision. Still usable for small models (7B Q4) on cards with sufficient VRAM like the GTX 1080 Ti (11 GB) or P40 (24 GB), but significantly slower than Turing and newer.
Buying advice
Excellent choice for local AI
Runs 26 of 50 top models well — a strong all-rounder for local inference.
24.0 GB
VRAM
$5,699
MSRP
$237/GB
Cost per GB VRAM
Best models for this GPU
What will limit you first
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
Best upgrade itinerary
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Unlocks 1 additional models that do not fit on the current setup.
Want more headroom? MacBook Pro M4 Max 36GB (36.0 GB unified memory) is the next step up.
Chat
SThis model is a direct match for chat. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.
Coding
SThis model is a direct match for coding. It belongs to a current frontier family for local AI. It should run, but memory headroom will be limited. Known channels: huggingface, ollama, lm-studio.
Agentic Coding
SThis model is still usable for agentic-coding, but it is not the most specialized pick. It belongs to a current frontier family for local AI. It should run, but memory headroom will be limited. Known channels: huggingface, lm-studio.
Reasoning
SThis model is a direct match for reasoning. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.
RAG
AThis model is a direct match for rag. It sits in the middle of the current model mix. It fits natively with comfortable headroom. Known channels: huggingface, ollama.
Just out of reach
High-quality models that need a bit more memory
Image & Video Generation
41 of 52 models can generate images or video on your Tesla P40 24GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | ~2.2s | S |
| Stable Diffusion 1.5Image | 512×768 | ~4.4s | S |
| Realistic Vision v5.1Image | 512×768 | ~4.4s | S |
| DreamShaper 8Image | 512×768 | ~4.4s | S |
| LCM DreamShaper v7Image | 512×768 | ~1.3s | S |
| PixArt-SigmaImage | 1024×1024 | ~17.6s | S |
| FramePack I2VVideo | 256×256 | ~32.3s/frame | S |
| SDXL TurboImage | 512×512 | ~2.2s | S |
| SDXL LightningImage | 1024×1024 | ~6.6s | S |
| Stable Diffusion XL 1.0Image | 1024×1024 | ~17.6s | S |
| Playground v2.5Image | 1024×1024 | ~26.4s | S |
| RealVisXL v5.0Image | 1024×1024 | ~19.8s | S |
| DreamShaper XLImage | 1024×1024 | ~19.8s | S |
| Juggernaut XL v9Image | 1024×1024 | ~19.8s | S |
| Animagine XL 3.1Image | 1024×1024 | ~19.8s | S |
| Pony Diffusion V6 XLImage | 1024×1024 | ~19.8s | S |
| Animagine XL 4.0Image | 1024×1024 | ~19.8s | S |
| Illustrious XLImage | 1024×1024 | ~19.8s | S |
| Wan Video 2.1 1.3BVideo | 256×256 | ~12.9s/frame | S |
| Stable Diffusion 3.5 MediumImage | 1024×1024 | ~30.8s | S |
| Flux.2 Klein 4BImage | 1024×1024 | ~5.3s | S |
| LTX Video 2BVideo | 768×512 | ~15.3s/frame | S |
| KolorsImage | 1024×1024 | ~35.2s | S |
| Stable CascadeImage | 1024×1024 | ~44s | S |
| AuraFlow v0.3Image | 1536×1536 | ~1m 19s | S |
| Stable Diffusion 3.5 LargeImage | 1024×1024 | ~1m 37s | S |
| Stable Diffusion 3.5 Large TurboImage | 1024×1024 | ~17.6s | S |
| CogVideoX 2BVideo | 720×480 | ~15.3s/frame | A |
| HunyuanVideoVideo | 256×256 | ~32.3s/frame | A |
| ChromaImage | 256×256 | ~32.3s | A |
| Z-Image TurboImage | 1536×1536 | ~18.2s | B |
| Flux.1 DevImage | 256×256 | ~1m 19s | B |
| Flux.1 SchnellImage | 256×256 | ~15.4s | B |
| LTX Video 13BVideo | 256×256 | ~32.3s/frame | B |
| Flux.1 Kontext DevImage | 256×256 | ~1m 28s | B |
| AnimateDiff v1.5.3Video | 512×768 | ~8s/frame | B |
| Cosmos Diffusion 7BVideo | 256×256 | ~48.7s/frame | B |
| CogVideoX 5BVideo | 256×256 | ~46.3s/frame | B |
| Wan2.2 TI2V 5BVideo | 256×256 | ~46.3s/frame | B |
| Flux.2 Klein 9BImage | 256×256 | ~16.1s | D |
| Flux.1 Fill DevImage | 256×256 | ~1m 15s | D |
| Mochi 1 PreviewVideo | 256×256 | ~29.1s/frame | F |
| HunyuanVideo 1.5Video | 256×256 | ~27s/frame | F |
| Helios 14BVideo | 256×256 | ~33.3s/frame | F |
| SkyReels V2 14BVideo | 256×256 | ~33.3s/frame | F |
| Wan Video 2.1 14BVideo | 256×256 | ~33.3s/frame | F |
| Wan Video 2.2 14BVideo | 256×256 | ~33.3s/frame | F |
| Qwen ImageImage | 256×256 | ~29.6s | F |
| Qwen Image EditImage | 256×256 | ~29.6s | F |
| Flux.2 DevImage | 256×256 | ~13m 53s | F |
| MAGI-1Video | 256×256 | ~41.3s/frame | F |
| HunyuanImage 3.0Image | 256×256 | ~52.2s | F |
Image models estimated at 1024×1024 (28 steps, FP16). Video models estimated at 768×512 (25 frames, 30 steps, FP16). Actual performance varies with runtime and system load.
Upgrade paths
See what you unlock with more powerful hardware
Upgrade options
Unlocks 1 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 33%.
~$2,499 MSRP
Unlocks 6 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 85%.
~$4,000 MSRP
Unlocks 17 additional models that do not fit on the current setup.
~$1,099 MSRP
Unlocks 45 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 372%.
~$8,000 MSRP
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