Best GPU for Local AI Mathematics
作者： Jakub Rusinowski · 最后更新： 2026年10月7日
Ranked for mathematics and quantitative work: Symbolic and numerical problem solving, proofs, and step-by-step quantitative reasoning.
Best overall: NVIDIA RTX 6000 Ada Generation
48 GB VRAM at 960 GB/s. It runs 132 of the models that qualify for this workload; the strongest is Qwen 3 32B at an estimated 32 tokens/sec.
The picks
| GPU | VRAM | MSRP | Models that fit | Best model it runs | Est. speed | |
|---|---|---|---|---|---|---|
| Best overall | NVIDIA RTX 6000 Ada Generation | 48 GB | $6,799 | 132 | Qwen 3 32B | ~32 tok/s |
| Best value | Intel Arc B570 | 10 GB | $219 | 91 | Qwen 3 14B | ~27.8 tok/s |
| Budget pick | Intel Arc B570 | 10 GB | $219 | 91 | Qwen 3 14B | ~27.8 tok/s |
| Most memory | NVIDIA DGX Spark | 128 GB | $4,699 | 143 | Qwen 3 32B | ~9.6 tok/s |
Full ranking for mathematics and quantitative work
| GPU | Score | VRAM | MSRP | Models fit | Est. speed | Tok/s per watt | Cost per model |
|---|---|---|---|---|---|---|---|
| NVIDIA RTX 6000 Ada Generation | 69.4 | 48 GB | $6,799 | 132 | ~32 | 0.11 | $52 |
| Intel Arc B580 | 67.6 | 12 GB | $249 | 92 | ~33 | 0.17 | $3 |
| NVIDIA L40S | 65.9 | 48 GB | $7,499 | 132 | ~29 | 0.08 | $57 |
| Intel Arc B570 | 65.2 | 10 GB | $219 | 91 | ~27.8 | 0.19 | $2 |
| NVIDIA GeForce RTX 5090 | 65.1 | 32 GB | $1,999 | 128 | ~57.4 | 0.1 | $16 |
| AMD Radeon RX 7800 XT | 65 | 16 GB | $499 | 102 | ~43.9 | 0.17 | $5 |
| AMD Radeon RX 9070 | 64.8 | 16 GB | $549 | 102 | ~44.9 | 0.2 | $5 |
| NVIDIA GeForce RTX 5070 | 64.3 | 12 GB | $549 | 92 | ~46.9 | 0.19 | $6 |
| NVIDIA RTX A6000 | 63.4 | 48 GB | $4,649 | 132 | ~26 | 0.09 | $35 |
| AMD Radeon RX 9070 XT | 63 | 16 GB | $599 | 102 | ~44.9 | 0.15 | $6 |
| NVIDIA GeForce RTX 3080 (10GB) | 61.8 | 10 GB | $699 | 91 | ~52.4 | 0.16 | $8 |
| NVIDIA GeForce RTX 5070 Ti | 61.6 | 16 GB | $749 | 102 | ~60.5 | 0.2 | $7 |
How these numbers are calculated
- GPUs are scored on four axes: capability (45%), speed (30%), value (20%) and efficiency (5%), each normalised across the whole ranking.
- Capability means the intrinsic strength of the best model the card can hold — not how many models fit, and not how fast it streams a small one.
- Speed is capped at 40 tok/s: past that, more throughput does not change how the model feels to use.
- Apple Silicon is excluded from this ranking. Those entries price a whole computer and rate a chip's package power, so on price-per-capability and performance-per-watt they would beat every add-in card by construction. Apple hardware is covered on the macOS platform page instead.
- The most concentrated capability weighting in the set: 85% reasoning, no creative weight at all. The quality floor of 70 is the highest anywhere here, because arithmetic and proof errors are silent — a plausible-looking wrong answer is worse than a refusal.
FAQ
What is the best GPU for mathematics and quantitative work?
The NVIDIA RTX 6000 Ada Generation — 48 GB of VRAM runs 132 qualifying models, the strongest being Qwen 3.
What is the cheapest GPU that works for mathematics and quantitative work?
The Intel Arc B570 at $219, which runs 91 qualifying models.
How much VRAM do I need for mathematics and quantitative work?
8 GB is the entry point at which a model for this workload will run at all. More memory buys a stronger model, not just a faster one.
What These GPUs Run
- Best models for the NVIDIA RTX 6000 Ada Generation
- Best models for the Intel Arc B570
- Best models for the NVIDIA DGX Spark