Hunyuan Hy4 vs Step 3.7 Flash

Tencent · China  |  StepFun · China · Updated June 2026

Quick verdict

Pick Hunyuan Hy4 for first hunyuan model with vision and computer use, adding image input to the text-only hy4 preview or tencent-reported gains over the preview of 19.1% on gamedev and 9.8% on gamelogic. Pick Step 3.7 Flash for a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows or scmp reported it 'outshines larger rivals' from deepseek and moonshot on some benchmarks despite its smaller active size. Choose Step 3.7 Flash if you need self-hosting or data privacy; Hunyuan Hy4 if you want a managed API.

Hunyuan Hy4 (Tencent) and Step 3.7 Flash (StepFun) are two of the models people most often weigh against each other in 2026. Hunyuan Hy4 is tencent's November 4, 2026 full Hy4 release - a 1M-context model that adds vision and computer use at about $0.90/$2.70, with weights promised but not yet public. Step 3.7 Flash is stepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecHunyuan Hy4Step 3.7 Flash
ProviderTencent (China) StepFun (China)
ReleasedNovember 4, 2026 May 29, 2026
Context window1M tokens (~1,573 pages) 256K (~393 pages)
Price (in/out)$0.9/$2.7 per 1M tokens $0.2/$1.15 per 1M tokens
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

First Hunyuan model with vision and computer use, adding image input to the text-only Hy4 Preview

Hunyuan Hy4

Tencent's November 4, 2026 full Hy4 release - a 1M-context model that adds vision and computer use at about $0.90/$2.70, with weights promised but not yet public — and it carries the larger 1M tokens context.

Tencent-reported gains over the preview of 19.1% on GameDev and 9.8% on GameLogic

Hunyuan Hy4

Tencent's November 4, 2026 full Hy4 release - a 1M-context model that adds vision and computer use at about $0.90/$2.70, with weights promised but not yet public — and it is the newer of the two.

Tencent-reported financial evaluation of 3.04, ahead of DeepSeek V4.1 Flash 1017 at 2.97

Hunyuan Hy4

Step 3.7 Flash is comparatively weak here — stepFun is a newer, less established lab than DeepSeek, Alibaba, or Moonshot

A 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows

Step 3.7 Flash

StepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights — and it runs cheaper at $0.2/$1.15 per 1M tokens.

SCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size

Step 3.7 Flash

StepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights — and its weights are open while Hunyuan Hy4 is API-only.

Open weights (Apache 2.0) at a low per-token price

Step 3.7 Flash

At $0.2/$1.15 per 1M tokens it undercuts Hunyuan Hy4 ($0.9/$2.7 per 1M tokens), and that gap compounds at volume.

Lowest cost at scale

Step 3.7 Flash

At $0.2/$1.15 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

Hunyuan Hy4

Its 1M tokens window is about 4× larger than Step 3.7 Flash's 256K, fitting roughly 1,573 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Step 3.7 Flash

At $0.2/$1.15 per 1M tokens it undercuts Hunyuan Hy4, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ Hunyuan Hy4

Larger 1M tokens window fits more in one prompt.

A team with data-privacy or self-hosting needs

→ Step 3.7 Flash

Open weights let you run it on your own hardware; Hunyuan Hy4 is API-only.

Anyone whose priority is first hunyuan model with vision and computer use, adding image input to the text-only hy4 preview

→ Hunyuan Hy4

It is specifically built for that.

Anyone whose priority is a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows

→ Step 3.7 Flash

That is its strongest area.

Hunyuan Hy4: where it fits

Tencent's November 4, 2026 full Hy4 release - a 1M-context model that adds vision and computer use at about $0.90/$2.70, with weights promised but not yet public. Released November 4, 2026 by Tencent, it is built for first Hunyuan model with vision and computer use, adding image input to the text-only Hy4 Preview, tencent-reported gains over the preview of 19.1% on GameDev and 9.8% on GameLogic, tencent-reported financial evaluation of 3.04, ahead of DeepSeek V4.1 Flash 1017 at 2.97, and about $0.90/$2.70 per million tokens, with 50% off on Tencent Cloud TokenHub through December 31, 2026 (OpenRouter lists $0.417/$1.25 with that discount).

Its trade-offs are real: weights not public as of November 5, 2026 - Tencent says weights and system cards will come in the coming days, and no license is announced yet, only the earlier Hy4 Preview is downloadable today (Apache 2.0), published improvements are Tencent's own and mostly relative to the preview, with no SWE-bench Verified figure, and sources differ on list price: Tencent says about $0.90/$2.70, while OpenRouter and Vals show $0.83/$2.50. At $0.9 in / $2.7 out per million tokens, it sits in the budget price band.

Step 3.7 Flash: where it fits

StepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights. Released May 29, 2026 by StepFun, it is built for a 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows, sCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size, open weights (Apache 2.0) at a low per-token price, and includes a 1.8B vision encoder for image understanding alongside text.

Its trade-offs: stepFun is a newer, less established lab than DeepSeek, Alibaba, or Moonshot, benchmark 'outshines rivals' claims are from press coverage of specific tests, not a full independent leaderboard sweep, and smaller ecosystem and less third-party documentation than the more established Chinese labs. At $0.2 in / $1.15 out per million tokens, it sits in the budget price band.

The bottom line for this matchup

The defining split here is open vs. closed. Step 3.7 Flash gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Hunyuan Hy4 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.

Want both Hunyuan Hy4 and Step 3.7 Flash without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.

See pricing

Frequently asked questions

Is Hunyuan Hy4 or Step 3.7 Flash better for coding?

Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Hunyuan Hy4 leans toward first hunyuan model with vision and computer use, adding image input to the text-only hy4 preview while Step 3.7 Flash leans toward a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Hunyuan Hy4 or Step 3.7 Flash?

Step 3.7 Flash is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Hunyuan Hy4 is API-metered at $0.9/$2.7 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.

Which has the bigger context window?

Hunyuan Hy4 — 1M tokens vs 256K, about 4× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Hunyuan Hy4 and Step 3.7 Flash together?

Yes — a multi-model platform like LumiChats gives you Hunyuan Hy4, Step 3.7 Flash and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.

Which is newer, Hunyuan Hy4 or Step 3.7 Flash?

Hunyuan Hy4 — released November 4, 2026, about 5 months after Step 3.7 Flash.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.