Intel Data Center GPU Max 1550
The Intel Data Center GPU Max 1550 has 128 GB VRAM and 3276 GB/s memory bandwidth. It can run 74 of our 99 tracked models natively in VRAM at 8k context.
With 128 GB HBM2e, the Intel Data Center GPU Max 1550 is a datacenter-tier GPU that can run 74 models natively.
The Intel Data Center GPU Max 1550 is Intel's flagship HPC accelerator with 128GB of HBM2e at 3,276 GB/s, enough to run 70B models at Q8 or larger 100B+ models at lower quantization entirely in GPU memory. It targets HPC and AI training workloads in supercomputing clusters via Intel's oneAPI/SYCL stack.
Intel Data Center GPU Max 1550: 2022 Xe-HPC Ponte Vecchio with 128GB HBM2e at 3,276 GB/s, Intel's top HPC accelerator.
70B at Q8 or 100B+ at lower quantizations fit in 128GB. Highest Intel bandwidth for inference.
SYCL/oneAPI gives best performance; llama.cpp SYCL backend supported. Typically cloud/HPC-accessed.
| Vendor | Intel |
| Architecture | Xe-HPC (Ponte Vecchio) |
| VRAM | 128 GB |
| Memory type | HBM2e |
| Memory bandwidth | 3276 GB/s |
| Compute backend | VULKAN |
| Tier | Datacenter |
| Released | 2022 |
| Models (native) | 74 / 99 |
| Models (offload) | 1 / 99 |
Need more than 128GB? Rent an H200 141GB from $3.59/hr ↗
Prices as of Oct 13, 2026. Rates change; check RunPod for current pricing. Affiliate link: CanItRun may earn a commission. Doesn't affect the fit calculation above.
Popular models for this GPU
Models this GPU runs natively in VRAM (74)
- DeepSeek V4 Flash 284B284B · MMLU-Pro 86.3Q2_K · ~87.6 t/s
- DeepSeek V4 Flash 0731 284B284B · MMLU-Pro N/AUD-IQ3_XXS · ~88.7 t/s
- Qwen3 235B-A22B (MoE)235B · MMLU-Pro 84.4Q2_K · ~41.3 t/s
- MiniMax M2.5 229B229B · MMLU-Pro 84.8Q2_K · ~64.6 t/s
- MiniMax M2.7 229B229B · MMLU-Pro 86.0Q2_K · ~64.6 t/s
Show 69 more
- Step 3.7 Flash198B · MMLU-Pro N/AQ3_K_M · ~76.5 t/s
- Step 3.5 Flash196.81B · MMLU-Pro 84.4Q3_K_M · ~76.5 t/s
- Qwen3.8-Flash-Next180B · MMLU-Pro N/AQ3_K_M · ~91.8 t/s
- Mixtral 8x22B Instruct v0.1141B · MMLU-Pro 40.0Q5_K_M · ~31.5 t/s
- Mistral Medium 3.5 128B128B · MMLU-Pro N/AQ6_K · ~11.9 t/s
- Qwen 3.5 122B-A10B (MoE)122B · MMLU-Pro 86.7Q6_K · ~67.6 t/s
- Nemotron 3 Super 120B120B · MMLU-Pro 83.7Q6_K · ~42.4 t/s
- GPT-OSS 120B117B · MMLU-Pro 80.7Q6_K · ~102.4 t/s
- Llama 4 Scout 109B109B · MMLU-Pro 74.3Q6_K · ~37.6 t/s
- GLM-4.5 Air 106B106B · MMLU-Pro 81.4Q6_K · ~60.2 t/s
- GLM-4.6V 106B106B · MMLU-Pro 79.9Q6_K · ~60.2 t/s
- Qwen 2.5 72B Instruct72B · MMLU-Pro 71.1Q8_0 · ~15.9 t/s
- Llama 3.3 70B Instruct70B · MMLU-Pro 68.9Q8_0 · ~16.3 t/s
- DeepSeek R1 Distill Llama 70B70B · MMLU-Pro 70.0Q8_0 · ~16.3 t/s
- Llama 3.1 70B Instruct70B · MMLU-Pro 66.4Q8_0 · ~16.3 t/s
- Mixtral 8x7B Instruct v0.146.7B · MMLU-Pro 29.7BF16 · ~39.3 t/s
- Command-R 35B35B · MMLU-Pro 33.0BF16 · ~16.3 t/s
- Qwen 3.5 35B-A3B (MoE)35B · MMLU-Pro 85.3BF16 · ~85.4 t/s
- Qwen 3.6 35B-A3B (MoE)35B · MMLU-Pro 85.2BF16 · ~85.4 t/s
- Ornith 1.5 35B-A3B (MoE)35B · MMLU-Pro N/ABF16 · ~85.4 t/s
- Yi 1.5 34B Chat34.4B · MMLU-Pro 37.0BF16 · ~18.1 t/s
- Qwen3 32B32.8B · MMLU-Pro 65.5BF16 · ~18.9 t/s
- Qwen 2.5 32B Instruct32.5B · MMLU-Pro 69.0BF16 · ~18.9 t/s
- Qwen 2.5 Coder 32B Instruct32.5B · MMLU-Pro 62.3BF16 · ~18.9 t/s
- DeepSeek R1 Distill Qwen 32B32.5B · MMLU-Pro 65.0BF16 · ~18.9 t/s
- Nemotron 3 Nano 30B32B · MMLU-Pro 78.3BF16 · ~72.5 t/s
- Gemma 4 31B30.7B · MMLU-Pro 85.2BF16 · ~20.2 t/s
- Qwen3 30B-A3B (MoE)30B · MMLU-Pro 61.5BF16 · ~73.4 t/s
- Nemotron 3.5 Lightning 30B-A3B30B · MMLU-Pro 81.6BF16 · ~70.4 t/s
- Muse Glimmer 30B27.8B · MMLU-Pro N/ABF16 · ~22.8 t/s
- Gemma 2 27B Instruct27.2B · MMLU-Pro 38.0BF16 · ~22.3 t/s
- Gemma 3 27B Instruct27B · MMLU-Pro 67.5BF16 · ~23 t/s
- Qwen 3.6 27B27B · MMLU-Pro 86.2BF16 · ~22.9 t/s
- UI-Mate 27B27B · MMLU-Pro ~86.2BF16 · ~22.9 t/s
- Bonsai 27B27B · MMLU-Pro ~81.5Ternary (Q2_0) · ~105.3 t/s
- Bonsai 2 27B27B · MMLU-Pro N/ATernary (Q2_0) · ~117 t/s
- Qwen 3.8 27B27B · MMLU-Pro N/ABF16 · ~22.9 t/s
- Gemma 4 26B (MoE)25.2B · MMLU-Pro 82.6BF16 · ~89 t/s
- Mistral Small 3.1 24B Instruct24B · MMLU-Pro 66.8BF16 · ~26 t/s
- Mistral Small 22B22.2B · MMLU-Pro 49.2BF16 · ~26.9 t/s
- GPT-OSS 20B21B · MMLU-Pro 67.9BF16 · ~102.7 t/s
- Qwen3 14B14.8B · MMLU-Pro 61.0BF16 · ~39.9 t/s
- Qwen 2.5 14B Instruct14.7B · MMLU-Pro 63.7BF16 · ~39.1 t/s
- Phi-4 14B Instruct14B · MMLU-Pro 70.4BF16 · ~41.5 t/s
- Mistral Nemo 12B Instruct12.2B · MMLU-Pro 35.6BF16 · ~47.1 t/s
- Gemma 3 12B Instruct12.2B · MMLU-Pro 60.6BF16 · ~47.3 t/s
- Gemma 4 12B (Unified)12B · MMLU-Pro 77.2BF16 · ~48.1 t/s
- Gemma 2 9B Instruct9.2B · MMLU-Pro 32.0BF16 · ~55.4 t/s
- Qwen 3.5 9B9B · MMLU-Pro 82.5BF16 · ~65.4 t/s
- Ornith 1.5 9B9B · MMLU-Pro N/ABF16 · ~65.4 t/s
- Llama 3.1 8B Instruct8B · MMLU-Pro 48.3BF16 · ~69.4 t/s
- DeepSeek R1 Distill Llama 8B8B · MMLU-Pro 41.0BF16 · ~69.4 t/s
- Qwen3 8B8B · MMLU-Pro 56.7BF16 · ~67.8 t/s
- Qwen 2.5 7B Instruct7.6B · MMLU-Pro 56.3BF16 · ~76.1 t/s
- Gemma 4 E4B7.52B · MMLU-Pro 69.4BF16 · ~108.5 t/s
- Mistral 7B Instruct v0.37.25B · MMLU-Pro 30.0BF16 · ~75.1 t/s
- Gemma 4 E2B4.65B · MMLU-Pro 60.0BF16 · ~181.6 t/s
- Gemma 3 4B Instruct4B · MMLU-Pro 43.6BF16 · ~124.7 t/s
- Phi-3.5 Mini Instruct3.8B · MMLU-Pro 47.4BF16 · ~101.7 t/s
- Phi-4-mini Instruct3.8B · MMLU-Pro 67.3BF16 · ~121 t/s
- Llama 3.2 3B Instruct3.2B · MMLU-Pro 24.0BF16 · ~141.9 t/s
- Qwen 2.5 3B Instruct3.1B · MMLU-Pro 32.4BF16 · ~144.6 t/s
- Gemma 2 2B Instruct2.6B · MMLU-Pro 17.8BF16 · ~166.6 t/s
- SmolLM2 1.7B Instruct1.7B · MMLU-Pro 19.0BF16 · ~195.9 t/s
- Qwen 2.5 1.5B Instruct1.5B · MMLU-Pro 16.8BF16 · ~247.1 t/s
- Llama 3.2 1B Instruct1.24B · MMLU-Pro 12.5BF16 · ~336.6 t/s
- Gemma 3 1B Instruct1B · MMLU-Pro 14.7BF16 · ~306.5 t/s
- Qwen 2.5 0.5B Instruct0.5B · MMLU-Pro 10.0BF16 · ~445.4 t/s
- SmolLM2 360M Instruct0.36B · MMLU-Pro 8.0BF16 · ~371.5 t/s
Models that fit with CPU offload (1)
These use system RAM for layers that don't fit in VRAM, so expect much slower inference.
Too large for this GPU (24)
- Llama 3.1 405B Instruct
- DeepSeek V3 671B
- DeepSeek R1 671B
- Llama 4 Maverick 400B
- MiniMax M1 456B
- GLM-4.5 355B
- GLM-4.6 355B
- GLM-4.7 358B
- GLM-5 744B
- Kimi K2.6
- GLM-5.1 754B
- DeepSeek V4 Pro 1.6T
- GLM-5.2 753B
- Nemotron 3 Ultra 550B-A55B
- MiMo V2.5 Pro
- Kimi K2.5
- MiniMax M3
- Inkling
- Kimi K3
- Qwen3.8 2.4T-A95B
- DeepSeek V4 Pro 0813 1.6T
- Ornith 1.5 397B (MoE)
- GLM-5.3 753B
- DeepSeek V4.1 Flash 552B
Frequently asked questions
- How much VRAM does the Intel Data Center GPU Max 1550 have?
- The Intel Data Center GPU Max 1550 has 128 GB of HBM2e with 3276 GB/s memory bandwidth.
- What is the Intel Data Center GPU Max 1550 best for?
- With 128 GB of VRAM, the Intel Data Center GPU Max 1550 is a server-class GPU that runs 70B-class dense models and large MoE models natively, with plenty of room for long context.
- What LLMs can the Intel Data Center GPU Max 1550 run locally?
- The Intel Data Center GPU Max 1550 can run 74 of the 99 open-weight models tracked by CanItRun natively in VRAM at 8k context. Top options include: Qwen3.8-Flash-Next at Q3_K_M, DeepSeek V4 Flash 0731 284B at UD-IQ3_XXS, Qwen 3.8 27B at BF16.
- Can the Intel Data Center GPU Max 1550 run Gemma 4 31B?
- Yes. The Intel Data Center GPU Max 1550 runs Gemma 4 31B natively in VRAM at BF16 quantization, achieving approximately 20.2 tokens per second.
- Can the Intel Data Center GPU Max 1550 run Qwen 3.6 27B?
- Yes. The Intel Data Center GPU Max 1550 runs Qwen 3.6 27B natively in VRAM at BF16 quantization, achieving approximately 22.9 tokens per second.
- Can the Intel Data Center GPU Max 1550 run Qwen3 8B?
- Yes. The Intel Data Center GPU Max 1550 runs Qwen3 8B natively in VRAM at BF16 quantization, achieving approximately 67.8 tokens per second.