StepFun promised the open weights for Step 5 Preview on October 15. On the morning of October 15, the Hugging Face repo returned a 404.
The weights landed later that same day. But the four-hour gap between the promise and the delivery is the most useful part of this story — because it tells you exactly how to read everything else about this release: the 8,000 tokens/sec/GPU headline, the benchmark table, and the price tag. All of it is real, and all of it comes with a vendor attached.
This is analysis only. We did not run, time, or benchmark anything in this article. Every number below is attributed to the source that published it.
What actually happened on October 15
StepFun announced Step 5 Preview on September 20, 2026, with API access live the same day and open weights promised for October 15. When October 15 arrived, Forkast checked the expected Hugging Face repository — stepfun-ai/Step-5-Preview-BF16 — at 01:55 UTC and found a 404. No official repo, no license document, no weights.
By later on October 15, the weights were live on Hugging Face in three forms: FP8 (gated by manual approval), BF16, and NVFP4. The license shipped with them: the StepFun Model License 1.0, which allows free use, modification, and redistribution, with a "Powered by StepFun AI" notice required above 100M monthly active users or $20M monthly revenue.
So the promise was kept — just not on the schedule the promise implied. If you plan infrastructure around vendor release dates, that gap is the lesson: treat a vendor's date as a target with a risk premium, not a delivery confirmation.
What Step 5 Preview is
| Spec | Value |
|---|---|
| Architecture | Sparse Mixture-of-Experts (MoE) |
| Total parameters | 600B |
| Active parameters per token | 27B |
| Context window | 1M tokens (input) |
| Input | Text, image (API adds video) |
| Weight formats on Hugging Face | FP8, BF16, NVFP4 |
| API list price | $1.00 / $2.70 per 1M input / output tokens |
| License | StepFun Model License 1.0 |
The design is the story: 600B total parameters with only 27B active per token — about 4.5% of the network doing work on any given token. That is how a model this large can be priced at $1.00 per million input tokens. The API has been live since September 20, and Step 5 Preview has also been available through OpenRouter since October 8 at the same list price (with a $0.05 cached-input tier).
The 8,000 tokens/sec/GPU number, unpacked
The headline that traveled furthest: NVIDIA says the NVFP4 version of Step 5 Preview runs at nearly 8,000 tokens per second per GPU on GB300 hardware.
Read it carefully, because every word in that sentence is doing work:
- "NVIDIA says" — this is a vendor serving claim, not an independent measurement. Nobody outside NVIDIA and StepFun has published a reproduced number as of this writing.
- "NVFP4" — this is the 4-bit quantized version, not the BF16 weights. Quantization buys throughput; whether it costs you accuracy on your workload is something you measure yourself, on your own prompts.
- "per GPU" — this is aggregate throughput across batched sequences, not the speed of one conversation. A single sequence does not decode at 8,000 tok/s. Total throughput rises with batching until the KV cache runs out.
- "on GB300" — flagship datacenter hardware. It says nothing about what the model does on the GPU you actually own.
None of that makes the number fake. It makes it a ceiling measured under ideal conditions by the vendor with the most to gain from it being large. The correct way to use it: as the top end of the range when you size a deployment, and as a reason to benchmark on your own traces before budgeting around it.
One more sizing reality check: one comparison table lists a 4x B300 (FP8) setup as the minimum self-host configuration. A 600B model is not a download-and-run-on-your-laptop release. The weights are open; the hardware to serve them is not cheap.
What a developer can actually do with it
Two routes, separated by cost and control:
Route 1: the API. Call it through StepFun's API or OpenRouter. At $1.00 per million input tokens and $2.70 per million output tokens, a million-token agentic session costs roughly $1 in input plus whatever it generates. If you only need inference, price this route first — it is live now, and you pay for tokens, not GPUs.
Route 2: the weights. Pull FP8, BF16, or NVFP4 from Hugging Face and serve them yourself with vLLM or SGLang. You get full control — custom routing, no per-token bill, no vendor API in your critical path — and you take on the hardware, the serving stack, and the quantization validation. This route fits when you have steady, high-volume inference that justifies dedicated GPUs, or when you need the model inside your own boundary.
The license matters here too: read the StepFun Model License 1.0 before pulling weights into anything commercial. The "Powered by StepFun AI" notice threshold (100M monthly active users or $20M monthly revenue) will not bite most projects — but the check takes two minutes, and skipping it is how teams inherit legal surprises.
Where it sits
StepFun's own comparison chart, as transcribed by MarkTechPost, places Step 5 Preview against GLM-5.3 and Kimi K3. The critical caveat, stated on the chart itself: Step 5 Preview ran at its High reasoning effort while rivals ran at Max — so these are not like-for-like comparisons.
| Benchmark | Step 5 Preview | GLM-5.3 | Kimi K3 |
|---|---|---|---|
| DeepSWE v1.1 (StepFun-reported) | 67.7 | 66.9 | 67.5 |
| Terminal-Bench 4.0 (StepFun-reported) | 33.3 | 41.9 | 12.6 |
| API price per 1M in/out | $1.00 / $2.70 | Not disclosed | $3.00 / $15.00 |
Independent numbers exist too: Artificial Analysis scores Step 5 Preview at 43.7 on its Intelligence Index (often rounded to 44). On that independent scale it sits near the top of the open-weight field — without StepFun holding the pen.
The honest read: this is a genuinely competitive open-weight release at a genuinely low price, with a benchmark table that flatters it by comparing different effort settings. The independent score backs up the rough picture, not the exact margins.
What to do with it
- Read the model card and license before you pull weights. The FP8 checkpoint is gated by manual approval; the license has a notice threshold. Two minutes now beats a compliance conversation later.
- If you only need inference, price the API route first. The weights are for people with hardware and volume. Everyone else is buying GPUs to save on tokens they could have bought directly.
- Treat vendor throughput as a ceiling, not a plan. Benchmark NVFP4 on your own prompts, at your own batch sizes, before you promise anyone a number.
- Do not trust launch dates. October 15 arrived with a 404. The weights still came. Plan for the slip, not the announcement.
Sources
- RuntimeWire, Oct 15, 2026 — weights on Hugging Face; NVIDIA's NVFP4 / GB300 claim (primary source: NVIDIA AI)
- Forkast, Oct 15, 2026 — repo 404 at 01:55 UTC on launch day
- CellCog — HF repos (FP8 gated, BF16, NVFP4); OpenRouter since Oct 8; license terms
- MarkTechPost, Oct 16, 2026 — StepFun comparison chart (DeepSWE, Terminal-Bench, prices); Artificial Analysis Intelligence Index 43.7
- Artificial Analysis / OpenRouter — independent Intelligence Index score
Every number in this article was verified against a source opened during this run. Benchmark figures are company-reported unless marked independent.
Decoding AI: AI news + tools, tested with hard numbers. What shipped, what it costs, what actually works. More at https://decodingaitools.substack.com
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