AI Compute Card Full Comparison Table (81 Featured · 252 in Database)
Data as of 2026-10-14. Specs follow each chip profile (chips.json) and pricing.json as the single source of truth. Legend: ✅ Available · 🔄 Announced/shipping soon · 🔮 Forward-looking (analyst estimates, for reference only).
Want a custom comparison? Try the interactive comparison tool (pick any chips to compare side-by-side) and the TCO calculator (5-year total cost of ownership); head-to-head deep dives live in the "🔥 Chip Comparisons" sidebar category.
Quick Filter
| Scenario | Recommended Models |
|---|
| Trillion-parameter training (GPT-4 class) | Rubin R200, B300 Ultra, MI400, TPU Ironwood |
| 10B–100B parameter training | H100, H200, B200, MI300X, MI325X |
| China market (domestic alternatives) | Ascend 950DT, Ascend 910C, Ascend 920, MLU690 |
| High-throughput inference | L40S, L4, H200 (inference mode), Crescent Island |
| Edge AI | Jetson Orin, Edge TPU, Hailo-8L |
Datacenter Training GPU
Compute is labeled with precision and sparse/dense convention, consistent with each chip profile.
| Model | FP8/FP4 Compute | FP16 Compute | Memory | Memory Bandwidth | TDP | Release | Status |
|---|
| NVIDIA Rubin R200 | 50,000 TFLOPS (NVFP4) | 4,000 TFLOPS (dense) | 288GB HBM4 | 19.2 TB/s | 1,800W | 2026 H1 | ✅ |
| NVIDIA B300 Ultra | 20,000 TFLOPS (FP4 sparse) | 5,000 TFLOPS (sparse) | 288GB HBM3e | 8 TB/s | 1,400W | 2026 H1 | ✅ |
| NVIDIA GB300 | 40,000 TFLOPS (FP4, Superchip) | 10,000 TFLOPS (Superchip) | 576GB HBM3e (2× B300) | 8 TB/s | 3,000W (Superchip) | 2025 Q1 | ✅ |
| NVIDIA B200 | 20,000 TFLOPS (FP4 sparse) | 5,000 TFLOPS (sparse) | 192GB HBM3e | 8 TB/s | 1,000W | 2025 Q2 | ✅ |
| NVIDIA GB200 | 40,000 TFLOPS (FP4, Superchip) | 10,000 TFLOPS (Superchip) | 192GB×2 HBM3e | 8 TB/s | 2,000W (Superchip) | 2024 Q4 | ✅ |
| NVIDIA B100 | 14,000 TFLOPS (FP4 sparse) | 3,500 TFLOPS (sparse) | 192GB HBM3e | 8 TB/s | 700W | 2024 Q4 | ✅ |
| NVIDIA H200 | 3,958 TFLOPS (sparse) | 1,979 TFLOPS | 141GB HBM3e | 4.8 TB/s | 700W | 2024 Q2 | ✅ |
| NVIDIA H100 SXM | 3,958 TFLOPS (sparse) | 1,979 TFLOPS | 80GB HBM3 | 3.35 TB/s | 700W | 2022 Q3 | ✅ |
| NVIDIA H20 | 296 TFLOPS | 148 TFLOPS | 96GB HBM3 | 4.0 TB/s | 400W | 2024 Q1 | ✅ |
| NVIDIA A100 | — | 312 TFLOPS | 80GB HBM2e | 2.0 TB/s | 300-400W | 2020 Q3 | ✅ |
| AMD MI400 Series | 40,000 TFLOPS (FP4) | 10,000 TFLOPS | 432GB HBM4 | 19.6 TB/s | 1,200-1,500W | 2026 H2 | 🔮 |
| AMD MI455X | 40,300 TFLOPS (MXFP4) | 10,100 TFLOPS (sparse) | 432GB HBM4 | 23.3 TB/s | Undisclosed | 2026 H2 | 🔄 |
| AMD MI350X | 10,100 TFLOPS (MXFP4) | 2,500 TFLOPS | 288GB HBM3e | 8 TB/s | 1,400W | 2025 H2 | ✅ |
| AMD MI325X | 2,614 TFLOPS | 1,307 TFLOPS | 256GB HBM3e | 6.48 TB/s | 750W | 2024 Q4 | ✅ |
| AMD MI300X | 2,614 TFLOPS | 1,307 TFLOPS | 192GB HBM3 | 5.3 TB/s | 750W | 2023 Q4 | ✅ |
| Huawei Ascend 950PR | 1,784 TFLOPS (MXFP4) | 486 TFLOPS | 128GB HiBL 1.0 | 1.6 TB/s | 600W | 2026 Q1 | ✅ |
| Huawei Ascend 950DT | 2,007 TFLOPS (MXFP4) | 547 TFLOPS | 144GB HiZQ 2.0 | 4 TB/s | 500W | 2026 Q3 | 🔄 |
| Huawei Ascend 920 | — | 900 TFLOPS | Undisclosed (HBM3) | 4 TB/s | Undisclosed | 2025 H2 | ✅ |
| Huawei Ascend 910C | — | 800 TFLOPS | 128GB HBM2e (dual-die) | 3.2 TB/s | 600W | 2025 Q1 | ✅ |
| Huawei Ascend 910B | — | 256 TFLOPS | 64GB HBM2e | 1.2 TB/s | 310W | 2023 | ✅ |
| Cambricon MLU690 | — | 700+ TFLOPS | 196GB HBM3 | 3.35 TB/s | ~500W | 2025 | ✅ |
| Moore Threads MTT S5000 | — | 400 TFLOPS | 80GB | 1.6 TB/s | 500W | 2025 Q1 | ✅ |
| MetaX C600 | 1,000 TFLOPS (FP8) | 500 TFLOPS | 144GB HBM3e | 3.6 TB/s | 400W | 2025 Q4 | ✅ |
| Kunlun P800 | — | 345 TFLOPS | 96GB HBM3 | 2.4 TB/s | 400W | 2024 Q1 | ✅ |
| Iluvatar BI-V150 | — | 192 TFLOPS | 64GB HBM2e | 1.2 TB/s | 350W | 2023 | ✅ |
Domestic chip note: Huawei Ascend, Cambricon MLU, Moore Threads MTT, MetaX, Kunlun, and Iluvatar are Chinese domestic AI chip representatives, primarily targeting the China market due to US export controls. MTT S5000 is priced in CNY (¥80,000).
Datacenter Inference GPU
AI Training ASIC (TPU / Gaudi / Trainium)
Wafer-Scale Training
Edge AI & On-Device NPU
Innovative Architectures
| Model | Architecture Type | Key Feature | Vendor | Status |
|---|
| Groq LPU v2 | LPU (Language Processing Unit) | Ultra-low latency inference (~500 tok/s) | Groq | ✅ |
| Graphcore IPU (Bow) | IPU (Intelligence Processing Unit) | Native graph computing, 1,400 IPU cores | Graphcore | ✅ |
| Tesla Dojo (D1) | Distributed training wafer | Integrated auto-labeling + model training | Tesla | ✅ |
| Apple M5 Ultra | SoC + NPU | On-device 50 TOPS, unified memory | Apple | 🔮 |
| BrainChip Akida 2 | Spiking Neural Network (SNN) | Ultra-low-power neuromorphic | BrainChip | ✅ |
Pricing Reference
Prices fluctuate with market supply and demand. Purchase prices are affected by export controls. CNY denotes Chinese domestic chip pricing in RMB (reference rate: 1 USD ≈ 7.2 CNY). Data for reference only.
NVIDIA
| Model | MSRP (USD) | Market Price (USD) | Notes |
|---|
| Rubin R200 | $85,000 | — | Estimated |
| GB300 | $75,000 | $72,000 | |
| GB200 | $65,000 | $62,000 | |
| B300 Ultra | $55,000 | $52,000 | |
| B200 | $45,000 | $42,000 | |
| B100 | $38,000 | $35,000 | |
| H200 | $40,000 | $38,000 | |
| H100 | $30,000 | $28,000 | |
| H100 NVL | $40,000 | $38,000 | |
| H20 | $14,000 | $13,000 | China-specific |
| A100 | $15,000 | $28,000 | Secondary market |
| L40S | $7,000 | $6,500 | |
| RTX Pro 6000 Blackwell | $6,800 | $6,500 | |
| RTX 6000 Ada | $4,500 | $4,200 | |
| RTX 5090 | $2,000 | $1,900 | |
| L4 / L2 | $2,500 | $2,300 | |
| T4 | $2,500 | $1,800 | Secondary market |
| Jetson Thor | $800 | — | Module |
| Jetson Orin | $400 | $380 | Module |
| H800 | — | — | CNY ¥280,000 / ¥250,000 (China market, 2023 data) |
AMD
| Model | MSRP (USD) | Market Price (USD) | Notes |
|---|
| MI400 | $55,000 | — | Estimated |
| MI350X | $40,000 | $37,000 | |
| MI355X | $22,000 | $20,500 | |
| MI325X | $18,000 | $16,500 | |
| MI300X | $15,000 | $13,500 | |
| MI250 | $12,000 | $10,000 | Secondary market |
| MI210 | $9,000 | $8,500 | |
Intel
| Model | MSRP (USD) | Market Price (USD) | Notes |
|---|
| Gaudi 4 | $25,000 | — | Estimated |
| Gaudi 3 | $18,000 | $16,500 | |
| Gaudi 2 | $12,000 | $11,000 | |
| Gaudi 1 | $8,000 | $7,000 | Discontinued |
| Max Series | $4,000 | $3,700 | |
| Flex Series | $1,000 | $900 | |
| Arc Pro B60 | $500 | $480 | |
| Arc Pro B50 | $350 | $330 | |
Huawei Ascend
| Model | MSRP (USD) | Market Price (USD) | Notes |
|---|
| Ascend 950DT | — | ¥250,000 | CNY channel price (2026-09, +20~50% vs July) |
| Ascend 950PR | — | ¥80,000 | CNY channel price (2026-09) |
| Ascend 910D | $18,000 | $16,000 | |
| Ascend 920 | $25,000 | $23,000 | |
| Ascend 910C | $16,000 | $14,500 | |
| Ascend 910B | $12,000 | $10,500 | |
Google TPU / AWS / Cloud
| Model | MSRP (USD) | Market Price (USD) | Notes |
|---|
| TPU Ironwood | $45,000 | — | Estimated |
| TPU v6p | $40,000 | — | |
| TPU v5p | $35,000 | — | |
| TPU v6e | $22,000 | — | |
| TPU v5e | $18,000 | — | |
| TPU v4 | $25,000 | — | |
| Trainium 3 | $30,000 | — | |
| Trainium 2 | $22,000 | — | |
| Inferentia 2 | $12,000 | — | |
| Trainium 1 | $15,000 | — | |
| Inferentia 1 | $8,000 | — | |
Chinese Domestic Chips (CNY Pricing)
| Model | MSRP (CNY) | Market Price (CNY) | USD Equivalent |
|---|
| Cambricon MLU690 | ¥190,000 | ¥175,000 | ~$24,306 |
| Moore Threads MTT S5000 | ¥80,000 | ¥75,000 | ~$10,417 |
| Iluvatar Bi-V150 | ¥85,000 | ¥78,000 | ~$10,833 |
| Enflame T21 | ¥70,000 | ¥65,000 | ~$9,028 |
| MetaX C500 | ¥55,000 | ¥52,000 | ~$7,222 |
| Moore Threads S4000 | ¥60,000 | ¥55,000 | ~$7,639 |
Other Vendors
| Model | MSRP (USD) | Market Price (USD) | Notes |
|---|
| Cerebras CS-4 rack system | $8,000,000 | — | Rack system (3× WSE-3 Turbo) |
| Cerebras WSE-3 | $5,000,000 | — | Rack system |
| Cerebras WSE-2 | $3,000,000 | — | Rack system |
| SambaNova SN40L | $200,000 | — | System |
| Groq LPU v2 | $35,000 | — | |
| Rubin Ultra | $150,000 | — | Estimated (announced GTC 2026, specs TBD) |
| Graphcore IPU | $15,000 | — | |
| Tenstorrent Blackhole | $20,000 | — | |
| Qualcomm AI 100 | $8,000 | $7,000 | |
| Hailo-8L | $300 | $280 | Module |
Purchasing Guide
By Model Scale
By Region
- North America / Europe: NVIDIA + AMD, freely available
- China: Ascend 950 / 910C / 920 / Cambricon MLU690 (domestic alternatives)
- Cloud (no hardware preference): Any vendor, choose by price
← Back to Home | Roadmap → | TCO Calculator → | Industry News →