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NVIDIA B100 SXM 192GB vs OpenAI Jalapeño

The B100 and the Jalapeño deliver near-identical FP8 throughput (3,500 vs 3,400 TFLOPS dense). The Jalapeño also carries 24 GB more memory (216 GB vs 192 GB).

B100: Blackwell, 2024 Jalapeño: Jalapeño, 2026
Memory
192 vs 216 GB
24 GB more for the Jalapeño
Bandwidth
8.0 TB/s vs 15.4 TB/s
Jalapeño moves data faster
TDP
700 W vs 700 W
Same power budget
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NVIDIA B100 SXM 192GB vs OpenAI Jalapeño

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NVIDIA B100 SXM 192GB

Full specs →

What is the NVIDIA B100?

The B100 is a GPU from NVIDIA on the Blackwell architecture, an accelerator for AI training, inference and high-performance computing. It is an SXM module, the mezzanine format used in dense multi-GPU servers. B100 full specifications →

Can I rent the B100 in the cloud?

Flopper is not tracking any live rental listings for the B100 yet. The provider directory lists the clouds that rent comparable accelerators on demand. GPU cloud providers →

How does the B100 compare with other accelerators?

This page sets the B100 against the Jalapeño. The B100 is the older generation of the two. This is a cross-vendor matchup, NVIDIA against OpenAI. Flopper also compares it head to head with the B200 SXM 180GB, across every published precision, memory and power. B100 vs B200 SXM 180GB →

Where do the B100 figures come from?

NVIDIA published the B100 figures in marketing material rather than a datasheet, and Flopper has no independent confirmation of them. How Flopper verifies specifications →

OpenAI logo

OpenAI Jalapeño

Full specs →

What is the OpenAI Jalapeño?

The Jalapeño is an ASIC from OpenAI on the Jalapeño architecture, an accelerator built for AI workloads. It has been announced but is not yet shipping. Jalapeño full specifications →

Can I rent the Jalapeño in the cloud?

Flopper is not tracking any live rental listings for the Jalapeño yet. The provider directory lists the clouds that rent comparable accelerators on demand. GPU cloud providers →

How does the Jalapeño compare with other accelerators?

This page sets the Jalapeño against the B100. The Jalapeño is the newer generation of the two. This is a cross-vendor matchup, OpenAI against NVIDIA. Flopper also compares it head to head with the GB300 NVL72 GPU 288GB, GB200 NVL72 GPU 186GB and Maia 200, across every published precision, memory and power. Jalapeño vs GB300 NVL72 GPU 288GB →

Where do the Jalapeño figures come from?

OpenAI published the Jalapeño figures in marketing material rather than a datasheet, and Flopper has no independent confirmation of them. How Flopper verifies specifications →

Specifications

B100
OpenAI logo
Jalapeño
Architecture
BlackwellJalapeño
Launch Year
20242026
Form Factor
SXMCustom
Memory
192 GB216 GB
Memory Bandwidth
8.0 TB/s15.4 TB/s
TDP
700 W700 W
Process Node
4nm—

Performance (TFLOPS)

B100
OpenAI logo
Jalapeño
30 TFLOPS No verified data available
60 TFLOPS No verified data available
875 TFLOPS
sparse not published
 No verified data available
1,750 TFLOPS
sparse not published
 No verified data available
1,750 TFLOPS
sparse not published
 No verified data available
3,500 TFLOPS
sparse not published
3,400 TFLOPS
FP6
No verified data available No verified data available
7,000 TFLOPS
sparse not published
13,400 TFLOPS
3,500 TOPS
sparse not published
 No verified data available

Figures are dense. Where a vendor publishes a figure it sits under the dense one and never decides a winner. Hover any precision for its definition, or read the GPU glossary.

FLOPS by Precision

What actually differs

The Jalapeño is the newer part: Jalapeño (2026) against the B100's Blackwell (2024).

The Jalapeño carries 24 GB more memory (216 GB against 192 GB), so larger models fit on one GPU before you shard. Bandwidth is 8.0 TB/s against 15.4 TB/s, which sets the ceiling on decode speed.

Power is 700 W against 700 W, and at FP32 the B100 does more work per watt. Weight the FP8 and FP16 rows for LLM work and the FP64 row for HPC.

New to the terms? The glossary explains FP64, FP32, TF32, BF16, FP16, FP8, FP4, INT8, Sparsity and TFLOPS. For how the generations relate, see NVIDIA architectures explained.

Frequently asked questions

Is the B100 faster than the Jalapeño?

They are close on paper: both deliver about 3,500 TFLOPS of dense FP8 throughput. Memory, bandwidth, and power are the deciding differences.

Which should you choose, the B100 or the Jalapeño?

On raw FP8 throughput the B100 and the Jalapeño are level, so the decision rests on memory, power and price. Choose the Jalapeño when the model has to fit on one GPU: it carries 24 GB more memory.

Which has more memory, the B100 or the Jalapeño?

The Jalapeño carries 216 GB of memory versus 192 GB for the B100. Memory bandwidth is 8.0 TB/s for the B100 and 15.4 TB/s for the Jalapeño.

How much power do the B100 and the Jalapeño draw?

The B100 is rated at 700 W TDP and the Jalapeño at 700 W. On FP32 throughput per watt, the B100 is the more efficient part.

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