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 Qwen3 235B A22B for deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux) or exceptional multilingual and alignment results (79.2 arena-hard v2, 85.2 writingbench). Choose Qwen3 235B A22B 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 Qwen3 235B A22B (Alibaba, 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. Qwen3 235B A22B is an older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Qwen3 235B A22B 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× more — 1M (~1,571 pages) vs 256K (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Qwen3 235B A22B is the newer model by about 3 months (released July 21, 2025), 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
Qwen3 235B A22B
Provider
OpenAI (US)
Alibaba (China)
Released
April 14, 2025
July 21, 2025
Context window
1M (~1,571 pages)
256K (~393 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× more than Qwen3 235B A22B's 256K in a single prompt.
Instruction following above its weight class — 84.1% on IFEval, beating GPT-4o: GPT-4.1 Mini — Qwen3 235B A22B is comparatively weak here — its 235B weights need roughly 438GB in BF16, far beyond consumer hardware
Multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini: 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.
Deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux): Qwen3 235B A22B — GPT-4.1 Mini is comparatively weak here — a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode
Exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench): Qwen3 235B A22B — An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding — and its weights are open while GPT-4.1 Mini is API-only.
Outstanding structured logic — 95.0 on ZebraLogic: Qwen3 235B A22B — An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding — and it is the newer of the two.
Lowest cost at scale: Qwen3 235B A22B — 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× larger than Qwen3 235B A22B's 256K, fitting roughly 1,571 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Qwen3 235B A22B — 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: Qwen3 235B A22B — 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 deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux): Qwen3 235B A22B — That is its strongest area.
An enterprise with regional data-residency rules: GPT-4.1 Mini or Qwen3 235B A22B — 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.
Qwen3 235B A22B: where it fits
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. Released July 21, 2025 by Alibaba, it is built for deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux), exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench), outstanding structured logic — 95.0 on ZebraLogic, and no thinking mode, which makes latency and token spend entirely predictable.
Its trade-offs: nearly a year old and superseded — Artificial Analysis now steers users to Qwen3.5-397B instead, text-only with no vision, and the absence of a thinking mode caps its hardest reasoning, coding is weak by 2026 standards, and it publishes no SWE-Bench score to compare on, and its 235B weights need roughly 438GB in BF16, far beyond consumer 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. Qwen3 235B A22B 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 Qwen3 235B A22B better for coding?
Public SWE-Bench figures are not available for Qwen3 235B A22B, 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 Qwen3 235B A22B leans toward deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4.1 Mini or Qwen3 235B A22B?
Qwen3 235B A22B 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× 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 Qwen3 235B A22B together?
Yes — a multi-model platform like LumiChats gives you GPT-4.1 Mini, Qwen3 235B A22B 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 Qwen3 235B A22B?
Qwen3 235B A22B — released July 21, 2025, about 3 months after GPT-4.1 Mini.
GPT-4.1 Mini vs Qwen3 235B A22B
OpenAI · US | Alibaba · 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 Qwen3 235B A22B for deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux) or exceptional multilingual and alignment results (79.2 arena-hard v2, 85.2 writingbench). Choose Qwen3 235B A22B 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 Qwen3 235B A22B (Alibaba, 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. Qwen3 235B A22B is an older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. 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: Qwen3 235B A22B 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× more — 1M (~1,571 pages) vs 256K (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Qwen3 235B A22B is the newer model by about 3 months (released July 21, 2025), 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
Qwen3 235B A22B
Provider
OpenAI (US)
Alibaba (China)
Released
April 14, 2025
July 21, 2025
Context window
1M (~1,571 pages)
256K (~393 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× more than Qwen3 235B A22B's 256K in a single prompt.
Instruction following above its weight class — 84.1% on IFEval, beating GPT-4o
GPT-4.1 Mini
Qwen3 235B A22B is comparatively weak here — its 235B weights need roughly 438GB in BF16, far beyond consumer hardware
Multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini
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.
Deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux)
Qwen3 235B A22B
GPT-4.1 Mini is comparatively weak here — a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode
Exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench)
Qwen3 235B A22B
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding — and its weights are open while GPT-4.1 Mini is API-only.
Outstanding structured logic — 95.0 on ZebraLogic
Qwen3 235B A22B
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding — and it is the newer of the two.
Lowest cost at scale
Qwen3 235B A22B
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× larger than Qwen3 235B A22B's 256K, fitting roughly 1,571 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen3 235B A22B
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
→ Qwen3 235B A22B
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 deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux)
→ Qwen3 235B A22B
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-4.1 Mini or Qwen3 235B A22B
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.
Qwen3 235B A22B: where it fits
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. Released July 21, 2025 by Alibaba, it is built for deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux), exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench), outstanding structured logic — 95.0 on ZebraLogic, and no thinking mode, which makes latency and token spend entirely predictable.
Its trade-offs: nearly a year old and superseded — Artificial Analysis now steers users to Qwen3.5-397B instead, text-only with no vision, and the absence of a thinking mode caps its hardest reasoning, coding is weak by 2026 standards, and it publishes no SWE-Bench score to compare on, and its 235B weights need roughly 438GB in BF16, far beyond consumer 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. Qwen3 235B A22B 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 Qwen3 235B A22B 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-4.1 Mini or Qwen3 235B A22B better for coding?
Public SWE-Bench figures are not available for Qwen3 235B A22B, 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 Qwen3 235B A22B leans toward deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4.1 Mini or Qwen3 235B A22B?
Qwen3 235B A22B 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× 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 Qwen3 235B A22B together?
Yes — a multi-model platform like LumiChats gives you GPT-4.1 Mini, Qwen3 235B A22B 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 Qwen3 235B A22B?
Qwen3 235B A22B — released July 21, 2025, about 3 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.