NVIDIA141 GB VRAM4,800 GB/s$4/hr

DeepSeek Coder V2 236B (MoE) on H200 SXM5 141GB: Does It Fit, How Fast, What It Costs

DeepSeek Coder V2 236B (MoE) at AWQ 4-bit needs 129.8 GB for its weights and 142.4 GB in total at 8K context with 8 concurrent users. That means it needs 2× H200 SXM5 141GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 2×
142.4 GB needed / 282 GB available
Decode speed
404.1
tok/s per stream
Aggregate
9699
tok/s @ 8 concurrent
Cost / 1M tokens
$0.2291
2× H200 SXM5 141GB
What changes as you add H200 SXM5 141GBs
Tensor-parallel degree vs VRAM, throughput, and cost. Cost scales linearly with GPU count; decode throughput scales near-linearly too, so cost per token stays roughly flat.
GPUsTotal VRAMVRAM neededDecode tok/sAggregate tok/sTTFTCost / 1M tokFits?
1× H200141 GB142.4 GB0.0000.000——✗
2× H200282 GB142.4 GB404.19699380.0 ms$0.2291✓
4× H200564 GB142.4 GB808.238795205.0 ms$0.1146✓
8× H2001128 GB142.4 GB1616155180117.5 ms$0.0573✓
Concurrency vs context length
On 2× H200 SXM5 141GB at AWQ 4-bit. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K193807.5 MB✓ fits
8K961.58 GB✓ fits
33K246.31 GB✓ fits
66K1212.62 GB✓ fits
131K625.23 GB✓ fits
Other GPUs that run DeepSeek Coder V2 236B (MoE)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB8×57934$0.0192
L40S 48GB4×6983$0.1114
A100 80GB SXM42×4041$0.1650
H100 SXM5 80GB2×6769$0.2052
AMD MI300X 192GB1×3150$0.2205
AMD MI325X 288GB1×3566$0.2727
Frequently asked questions

Can DeepSeek Coder V2 236B (MoE) run on H200 SXM5 141GB?

Yes, but it needs 2× H200 SXM5 141GB. At AWQ 4-bit the total footprint is 142.4 GB (129.8 GB of weights plus 12.6 GB of KV cache at 8K × 8 concurrent users), against 282 GB of available VRAM across 2 GPUs.

How fast is DeepSeek Coder V2 236B (MoE) on H200 SXM5 141GB?

404.1 tokens/sec per stream and 9699 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 380.0 ms, and inter-token latency is 2.5 ms.

What does DeepSeek Coder V2 236B (MoE) on H200 SXM5 141GB cost per million tokens?

$0.2291 per 1M output tokens at 2× H200 SXM5 141GB ($4.00/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does DeepSeek Coder V2 236B (MoE) need on H200 SXM5 141GB?

129.8 GB for the weights at AWQ 4-bit, plus 12.6 GB of KV cache for 8 concurrent requests at 8K context — 142.4 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is H200 SXM5 141GB the right choice for DeepSeek Coder V2 236B (MoE)?

It works. Compare $0.2291 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 5090 32GB at $0.0192, and the fastest is 4× Cerebras CS-3 (WSE-3) at 161646 tok/s.

Adjust the workload yourself

Same formulas, your context length, concurrency, and quantisation.

Open in calculator