NVIDIA H200 NVL
Hopper
- Memory
- 141 GB HBM3e
- Bandwidth
- 4.8 TB/s
- FP4 inference
- — (FP8 instead — 3,958 TFLOPS sparse)
- NVLink
- NVLink 4 (900 GB/s)
- Shipping
- Volume — 2024 onward
Available in
Compare / H200 vs B200 vs B300
The three NVIDIA GPUs you'll be quoted in 2026.
H200 (Hopper), B200 (Blackwell), B300 (Blackwell Ultra). Three price points, three shipping windows, three sweet spots. This is how we frame the choice for clients.
Spec sheet — at a glance
What you're actually buying.
NVIDIA B200
Blackwell
- Memory
- 180 GB HBM3e
- Bandwidth
- 8 TB/s
- FP4 inference
- 18 PFLOPS dense · 36 PFLOPS sparse
- NVLink
- NVLink 5 (1.8 TB/s)
- Shipping
- Volume — 2025 onward
Available in
NVIDIA B300
Blackwell Ultra
- Memory
- 288 GB HBM3e
- Bandwidth
- 8 TB/s+ (NVIDIA published)
- FP4 inference
- ~26 PFLOPS dense per GPU (NVIDIA published)
- NVLink
- NVLink 5 (1.8 TB/s)
- Shipping
- Ramping — 2025–2026
Available in
Workload fit
Which GPU wins for which workload?
Long-context reasoning (200K – 1M tokens)
- H200
- OK — KV cache pressure on 70B+
- B200
- Good
- B300
- Best — denser HBM3e per GPU
70B production inference
- H200
- Good — cheapest per token
- B200
- Better — FP4 changes economics
- B300
- Best — long-context headroom
70B–400B fine-tuning
- H200
- Possible with parallelism
- B200
- Good
- B300
- Best
Frontier training (>1T)
- H200
- Not the right tool
- B200
- Multi-node DGX SuperPOD
- B300
- GB300 NVL72 rack-scale
Cost-sensitive inference
- H200
- Best price/performance today
- B200
- Better tokens-per-MYR than H200
- B300
- Allocation-constrained
Buy now vs wait?
The honest read.
Order H200 today
You need 70B-class inference on a budget and your workload doesn't push the GPU memory ceiling. Best price/performance per token in 2025.
Order B200 today
You're refreshing in 2025–2026 and want the FP4 economics. Allocation is easier than B300, and you can step up to B300 later in the same DGX SuperPOD fabric.
Plan for B300
Reasoning workloads with long context dominate your roadmap, OR you specifically need GB300 NVL72 for rack-scale. Allocation conversation now.
Where this GPU lives in our lineup
Right GPU, wrong system class?
We pair the GPU choice with the right chassis and fabric.
02Talk to EMARQUE
Tell us about your workload.
Model size, concurrency, latency budget, deployment site. EMARQUE returns a quote in MYR within one Malaysian business day, sized to the workload — not the salesperson’s quota.
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Key Account Manager
+6012 627 2280 - 02
Request for Quotation
business@emarque.co