Pick GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work or classification, extraction, ranking and sub-agent execution at scale. Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). Choose Hunyuan Hy4 Preview if you need self-hosting or data privacy; GPT-5.4 Nano if you want a managed API.
GPT-5.4 Nano (OpenAI, US) and Hunyuan Hy4 Preview (Tencent, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. GPT-5.4 Nano is openAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. Hunyuan Hy4 Preview is tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: GPT-5.4 Nano is about 4.2× cheaper on input ($0.2/$1.25 per 1M tokens vs $0.834/$2.501 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: Hunyuan Hy4 Preview holds 2.5× more — 1M+ tokens (~1,500 pages) vs 400K (~600 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Hunyuan Hy4 Preview is the newer model by about 5 months (released August 28, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
GPT-5.4 Nano
Hunyuan Hy4 Preview
Provider
OpenAI (US)
Tencent (China)
Released
March 17, 2026
August 28, 2026
Context window
400K (~600 pages)
1M+ tokens (~1,500 pages)
Price (in/out)
$0.2/$1.25 per 1M tokens
$0.834/$2.501 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work: GPT-5.4 Nano — At $0.2/$1.25 per 1M tokens it undercuts Hunyuan Hy4 Preview ($0.834/$2.501 per 1M tokens), and that gap compounds at volume.
Classification, extraction, ranking and sub-agent execution at scale: GPT-5.4 Nano — OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning — and it runs cheaper at $0.2/$1.25 per 1M tokens.
A 400K context in the smallest, fastest GPT-5.4 variant: GPT-5.4 Nano — GPT-5.4 Nano lists a 400K context in the smallest, fastest GPT-5.4 variant among its strengths; Hunyuan Hy4 Preview does not.
GPQA Diamond (92.3): Hunyuan Hy4 Preview — Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline — and it carries the larger 1M+ tokens context.
Terminal-Bench (85.4): Hunyuan Hy4 Preview — GPT-5.4 Nano is comparatively weak here — no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead)
SWE-bench Multilingual (82.9): Hunyuan Hy4 Preview — Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline — and its weights are open while GPT-5.4 Nano is API-only.
Lowest cost at scale: GPT-5.4 Nano — At $0.2/$1.25 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 Preview — Its 1M+ tokens window is about 2.5× larger than GPT-5.4 Nano's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-5.4 Nano — At $0.2/$1.25 per 1M tokens it undercuts Hunyuan Hy4 Preview, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Hunyuan Hy4 Preview — Larger 1M+ tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs: Hunyuan Hy4 Preview — Open weights let you run it on your own hardware; GPT-5.4 Nano is API-only.
Anyone whose priority is cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work: GPT-5.4 Nano — It is specifically built for that.
Anyone whose priority is gpqa diamond (92.3): Hunyuan Hy4 Preview — That is its strongest area.
An enterprise with regional data-residency rules: GPT-5.4 Nano or Hunyuan Hy4 Preview — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GPT-5.4 Nano: where it fits
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. Released March 17, 2026 by OpenAI, it is built for cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, classification, extraction, ranking and sub-agent execution at scale, a 400K context in the smallest, fastest GPT-5.4 variant, and text and image input for cheap multimodal pipelines.
Its trade-offs are real: a nano tier — not built for hard reasoning or frontier coding, no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead), outclassed by GPT-5.4 and GPT-5.4 Mini whenever a task needs real depth, and image input only — no audio or video. At $0.2 in / $1.25 out per million tokens, it sits in the budget price band.
Hunyuan Hy4 Preview: where it fits
Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. Released August 28, 2026 by Tencent, it is built for gPQA Diamond (92.3), terminal-Bench (85.4), sWE-bench Multilingual (82.9), and large jump in long-horizon coding vs prior Hunyuan model (DeepSWE 28.0 to 64.3).
Its trade-offs: text-only, no native vision support, labeled a 'preview', not yet Tencent's finalized GA flagship, and sWE-Marathon score still low in absolute terms (31.9) despite a large relative jump. At $0.834 in / $2.501 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. Hunyuan Hy4 Preview gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.4 Nano 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.
Frequently asked questions
Is GPT-5.4 Nano or Hunyuan Hy4 Preview 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, GPT-5.4 Nano leans toward cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work while Hunyuan Hy4 Preview leans toward gpqa diamond (92.3), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 Nano or Hunyuan Hy4 Preview?
Hunyuan Hy4 Preview is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.4 Nano is API-metered at $0.2/$1.25 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 Preview — 1M+ tokens vs 400K, about 2.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.4 Nano and Hunyuan Hy4 Preview together?
Yes — a multi-model platform like LumiChats gives you GPT-5.4 Nano, Hunyuan Hy4 Preview 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, GPT-5.4 Nano or Hunyuan Hy4 Preview?
Hunyuan Hy4 Preview — released August 28, 2026, about 5 months after GPT-5.4 Nano.
GPT-5.4 Nano vs Hunyuan Hy4 Preview
OpenAI · US | Tencent · China · Updated June 2026
Quick verdict
Pick GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work or classification, extraction, ranking and sub-agent execution at scale. Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). Choose Hunyuan Hy4 Preview if you need self-hosting or data privacy; GPT-5.4 Nano if you want a managed API.
GPT-5.4 Nano (OpenAI, US) and Hunyuan Hy4 Preview (Tencent, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. GPT-5.4 Nano is openAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. Hunyuan Hy4 Preview is tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. 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
▸Price: GPT-5.4 Nano is about 4.2× cheaper on input ($0.2/$1.25 per 1M tokens vs $0.834/$2.501 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: Hunyuan Hy4 Preview holds 2.5× more — 1M+ tokens (~1,500 pages) vs 400K (~600 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Hunyuan Hy4 Preview is the newer model by about 5 months (released August 28, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
GPT-5.4 Nano
Hunyuan Hy4 Preview
Provider
OpenAI (US)
Tencent (China)
Released
March 17, 2026
August 28, 2026
Context window
400K (~600 pages)
1M+ tokens (~1,500 pages)
Price (in/out)
$0.2/$1.25 per 1M tokens
$0.834/$2.501 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work
GPT-5.4 Nano
At $0.2/$1.25 per 1M tokens it undercuts Hunyuan Hy4 Preview ($0.834/$2.501 per 1M tokens), and that gap compounds at volume.
Classification, extraction, ranking and sub-agent execution at scale
GPT-5.4 Nano
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning — and it runs cheaper at $0.2/$1.25 per 1M tokens.
A 400K context in the smallest, fastest GPT-5.4 variant
GPT-5.4 Nano
GPT-5.4 Nano lists a 400K context in the smallest, fastest GPT-5.4 variant among its strengths; Hunyuan Hy4 Preview does not.
GPQA Diamond (92.3)
Hunyuan Hy4 Preview
Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline — and it carries the larger 1M+ tokens context.
Terminal-Bench (85.4)
Hunyuan Hy4 Preview
GPT-5.4 Nano is comparatively weak here — no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead)
SWE-bench Multilingual (82.9)
Hunyuan Hy4 Preview
Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline — and its weights are open while GPT-5.4 Nano is API-only.
Lowest cost at scale
GPT-5.4 Nano
At $0.2/$1.25 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 Preview
Its 1M+ tokens window is about 2.5× larger than GPT-5.4 Nano's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-5.4 Nano
At $0.2/$1.25 per 1M tokens it undercuts Hunyuan Hy4 Preview, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Hunyuan Hy4 Preview
Larger 1M+ tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Hunyuan Hy4 Preview
Open weights let you run it on your own hardware; GPT-5.4 Nano is API-only.
Anyone whose priority is cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work
→ GPT-5.4 Nano
It is specifically built for that.
Anyone whose priority is gpqa diamond (92.3)
→ Hunyuan Hy4 Preview
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-5.4 Nano or Hunyuan Hy4 Preview
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GPT-5.4 Nano: where it fits
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. Released March 17, 2026 by OpenAI, it is built for cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, classification, extraction, ranking and sub-agent execution at scale, a 400K context in the smallest, fastest GPT-5.4 variant, and text and image input for cheap multimodal pipelines.
Its trade-offs are real: a nano tier — not built for hard reasoning or frontier coding, no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead), outclassed by GPT-5.4 and GPT-5.4 Mini whenever a task needs real depth, and image input only — no audio or video. At $0.2 in / $1.25 out per million tokens, it sits in the budget price band.
Hunyuan Hy4 Preview: where it fits
Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. Released August 28, 2026 by Tencent, it is built for gPQA Diamond (92.3), terminal-Bench (85.4), sWE-bench Multilingual (82.9), and large jump in long-horizon coding vs prior Hunyuan model (DeepSWE 28.0 to 64.3).
Its trade-offs: text-only, no native vision support, labeled a 'preview', not yet Tencent's finalized GA flagship, and sWE-Marathon score still low in absolute terms (31.9) despite a large relative jump. At $0.834 in / $2.501 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. Hunyuan Hy4 Preview gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.4 Nano 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 GPT-5.4 Nano and Hunyuan Hy4 Preview 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.
Is GPT-5.4 Nano or Hunyuan Hy4 Preview 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, GPT-5.4 Nano leans toward cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work while Hunyuan Hy4 Preview leans toward gpqa diamond (92.3), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 Nano or Hunyuan Hy4 Preview?
Hunyuan Hy4 Preview is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.4 Nano is API-metered at $0.2/$1.25 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 Preview — 1M+ tokens vs 400K, about 2.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.4 Nano and Hunyuan Hy4 Preview together?
Yes — a multi-model platform like LumiChats gives you GPT-5.4 Nano, Hunyuan Hy4 Preview 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, GPT-5.4 Nano or Hunyuan Hy4 Preview?
Hunyuan Hy4 Preview — released August 28, 2026, about 5 months after GPT-5.4 Nano.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.