Pick GPT-4.1 Mini for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens or instruction following above its weight class — 84.1% on ifeval, beating gpt-4o. Pick Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost or runs a 295b model at the cost of a 21b — only 21b parameters active per token. Choose Hunyuan Hy3 if you need self-hosting or data privacy; GPT-4.1 Mini if you want a managed API.
GPT-4.1 Mini (OpenAI, US) and Hunyuan Hy3 (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-4.1 Mini is a cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. Hunyuan Hy3 is a 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Hunyuan Hy3 ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-4.1 Mini is API-metered at $0.4/$1.6 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: GPT-4.1 Mini holds 4.1× more — 1M (~1,571 pages) vs 256K (~384 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 Hy3 is the newer model by about 15 months (released July 6, 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-4.1 Mini
Hunyuan Hy3
Provider
OpenAI (US)
Tencent (China)
Released
April 14, 2025
July 6, 2026
Context window
1M (~1,571 pages)
256K (~384 pages)
Price (in/out)
$0.4/$1.6 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
23.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Very cheap high-volume text work at $0.40 in / $1.60 out per million tokens: GPT-4.1 Mini — Its 1M window holds about 4.1× more than Hunyuan Hy3's 256K in a single prompt.
Instruction following above its weight class — 84.1% on IFEval, beating GPT-4o: GPT-4.1 Mini — A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT — and it carries the larger 1M context.
Multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini: GPT-4.1 Mini — GPT-4.1 Mini lists multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini among its strengths; Hunyuan Hy3 does not.
Frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost: Hunyuan Hy3 — GPT-4.1 Mini is comparatively weak here — a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode
Runs a 295B model at the cost of a 21B — only 21B parameters active per token: Hunyuan Hy3 — A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost — and its weights are open while GPT-4.1 Mini is API-only.
Clean, unrestricted Apache-2.0 license with no geographic carve-out: Hunyuan Hy3 — A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost — and it is the newer of the two.
Lowest cost at scale: Hunyuan Hy3 — Its weights are open, so at volume you pay for your own hardware instead of GPT-4.1 Mini's $0.4/$1.6 per 1M tokens.
Largest single-prompt input: GPT-4.1 Mini — Its 1M window is about 4.1× larger than Hunyuan Hy3's 256K, fitting roughly 1,571 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Hunyuan Hy3 — At Open weight (self-host / free) it undercuts GPT-4.1 Mini, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-4.1 Mini — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: Hunyuan Hy3 — Open weights let you run it on your own hardware; GPT-4.1 Mini is API-only.
Anyone whose priority is very cheap high-volume text work at $0.40 in / $1.60 out per million tokens: GPT-4.1 Mini — It is specifically built for that.
Anyone whose priority is frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost: Hunyuan Hy3 — That is its strongest area.
An enterprise with regional data-residency rules: GPT-4.1 Mini or Hunyuan Hy3 — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GPT-4.1 Mini: where it fits
A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. Released April 14, 2025 by OpenAI, it is built for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens, instruction following above its weight class — 84.1% on IFEval, beating GPT-4o, multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini, and a full 1M context at flat pricing, with no long-context premium.
Its trade-offs are real: weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%, retired from ChatGPT in February 2026, and OpenAI's own docs now point users to GPT-5 mini instead, and a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode. At $0.4 in / $1.6 out per million tokens, it sits in the budget price band.
Hunyuan Hy3: where it fits
A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Released July 6, 2026 by Tencent, it is built for frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost, runs a 295B model at the cost of a 21B — only 21B parameters active per token, clean, unrestricted Apache-2.0 license with no geographic carve-out, and broad day-one ecosystem support plus an FP8 checkpoint.
Its trade-offs: benchmarks are largely self-reported, and the ultra-low hosted pricing is a limited promotion, and the hosted API is China-jurisdiction, and self-hosting a 295B MoE still needs serious hardware. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
The defining split here is open vs. closed. Hunyuan Hy3 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-4.1 Mini 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-4.1 Mini or Hunyuan Hy3 better for coding?
Public SWE-Bench figures are not available for Hunyuan Hy3, so the honest test is your own repository — run an identical real bug through both. By design, GPT-4.1 Mini leans toward very cheap high-volume text work at $0.40 in / $1.60 out per million tokens while Hunyuan Hy3 leans toward frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4.1 Mini or Hunyuan Hy3?
Hunyuan Hy3 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-4.1 Mini is API-metered at $0.4/$1.6 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?
GPT-4.1 Mini — 1M vs 256K, about 4.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-4.1 Mini and Hunyuan Hy3 together?
Yes — a multi-model platform like LumiChats gives you GPT-4.1 Mini, Hunyuan Hy3 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-4.1 Mini or Hunyuan Hy3?
Hunyuan Hy3 — released July 6, 2026, about 15 months after GPT-4.1 Mini.
GPT-4.1 Mini vs Hunyuan Hy3
OpenAI · US | Tencent · China · Updated June 2026
Quick verdict
Pick GPT-4.1 Mini for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens or instruction following above its weight class — 84.1% on ifeval, beating gpt-4o. Pick Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost or runs a 295b model at the cost of a 21b — only 21b parameters active per token. Choose Hunyuan Hy3 if you need self-hosting or data privacy; GPT-4.1 Mini if you want a managed API.
GPT-4.1 Mini (OpenAI, US) and Hunyuan Hy3 (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-4.1 Mini is a cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. Hunyuan Hy3 is a 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. 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
▸Cost model: Hunyuan Hy3 ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-4.1 Mini is API-metered at $0.4/$1.6 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: GPT-4.1 Mini holds 4.1× more — 1M (~1,571 pages) vs 256K (~384 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 Hy3 is the newer model by about 15 months (released July 6, 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-4.1 Mini
Hunyuan Hy3
Provider
OpenAI (US)
Tencent (China)
Released
April 14, 2025
July 6, 2026
Context window
1M (~1,571 pages)
256K (~384 pages)
Price (in/out)
$0.4/$1.6 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
23.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Very cheap high-volume text work at $0.40 in / $1.60 out per million tokens
GPT-4.1 Mini
Its 1M window holds about 4.1× more than Hunyuan Hy3's 256K in a single prompt.
Instruction following above its weight class — 84.1% on IFEval, beating GPT-4o
GPT-4.1 Mini
A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT — and it carries the larger 1M context.
Multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini
GPT-4.1 Mini
GPT-4.1 Mini lists multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini among its strengths; Hunyuan Hy3 does not.
Frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost
Hunyuan Hy3
GPT-4.1 Mini is comparatively weak here — a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode
Runs a 295B model at the cost of a 21B — only 21B parameters active per token
Hunyuan Hy3
A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost — and its weights are open while GPT-4.1 Mini is API-only.
Clean, unrestricted Apache-2.0 license with no geographic carve-out
Hunyuan Hy3
A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost — and it is the newer of the two.
Lowest cost at scale
Hunyuan Hy3
Its weights are open, so at volume you pay for your own hardware instead of GPT-4.1 Mini's $0.4/$1.6 per 1M tokens.
Largest single-prompt input
GPT-4.1 Mini
Its 1M window is about 4.1× larger than Hunyuan Hy3's 256K, fitting roughly 1,571 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Hunyuan Hy3
At Open weight (self-host / free) it undercuts GPT-4.1 Mini, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-4.1 Mini
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Hunyuan Hy3
Open weights let you run it on your own hardware; GPT-4.1 Mini is API-only.
Anyone whose priority is very cheap high-volume text work at $0.40 in / $1.60 out per million tokens
→ GPT-4.1 Mini
It is specifically built for that.
Anyone whose priority is frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost
→ Hunyuan Hy3
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-4.1 Mini or Hunyuan Hy3
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GPT-4.1 Mini: where it fits
A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. Released April 14, 2025 by OpenAI, it is built for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens, instruction following above its weight class — 84.1% on IFEval, beating GPT-4o, multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini, and a full 1M context at flat pricing, with no long-context premium.
Its trade-offs are real: weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%, retired from ChatGPT in February 2026, and OpenAI's own docs now point users to GPT-5 mini instead, and a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode. At $0.4 in / $1.6 out per million tokens, it sits in the budget price band.
Hunyuan Hy3: where it fits
A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Released July 6, 2026 by Tencent, it is built for frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost, runs a 295B model at the cost of a 21B — only 21B parameters active per token, clean, unrestricted Apache-2.0 license with no geographic carve-out, and broad day-one ecosystem support plus an FP8 checkpoint.
Its trade-offs: benchmarks are largely self-reported, and the ultra-low hosted pricing is a limited promotion, and the hosted API is China-jurisdiction, and self-hosting a 295B MoE still needs serious hardware. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
The defining split here is open vs. closed. Hunyuan Hy3 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-4.1 Mini 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-4.1 Mini and Hunyuan Hy3 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.
Public SWE-Bench figures are not available for Hunyuan Hy3, so the honest test is your own repository — run an identical real bug through both. By design, GPT-4.1 Mini leans toward very cheap high-volume text work at $0.40 in / $1.60 out per million tokens while Hunyuan Hy3 leans toward frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4.1 Mini or Hunyuan Hy3?
Hunyuan Hy3 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-4.1 Mini is API-metered at $0.4/$1.6 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?
GPT-4.1 Mini — 1M vs 256K, about 4.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-4.1 Mini and Hunyuan Hy3 together?
Yes — a multi-model platform like LumiChats gives you GPT-4.1 Mini, Hunyuan Hy3 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-4.1 Mini or Hunyuan Hy3?
Hunyuan Hy3 — released July 6, 2026, about 15 months after GPT-4.1 Mini.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.