GPT-4.1 Mini vs Kimi K3

OpenAI · US  |  Moonshot AI · 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 Kimi K3 for largest open-weight model at release — 2.8t sparse moe, self-hostable or 1m-token context with native vision (text, image and video). Choose Kimi K3 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 Kimi K3 (Moonshot AI, 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. Kimi K3 is moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores. 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

SpecGPT-4.1 MiniKimi K3
ProviderOpenAI (US) Moonshot AI (China)
ReleasedApril 14, 2025 July 27, 2026
Context window1M (~1,571 pages) 1M (~1,573 pages)
Price (in/out)$0.4/$1.6 per 1M tokens $3/$15 per 1M tokens
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, code text, image, video, code
SWE-Bench Verified23.6% Not published
MRCR v2 @ 1MNot 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

At $0.4/$1.6 per 1M tokens it undercuts Kimi K3 ($3/$15 per 1M tokens), and that gap compounds at volume.

Instruction following above its weight class — 84.1% on IFEval, beating GPT-4o

GPT-4.1 Mini

Kimi K3 is comparatively weak here — 2.8T params need serious hardware to self-host — weights are free, running is not

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 runs cheaper at $0.4/$1.6 per 1M tokens.

Largest open-weight model at release — 2.8T sparse MoE, self-hostable

Kimi K3

Open weights make this possible at all — GPT-4.1 Mini is API-only, so it cannot leave the vendor's servers.

1M-token context with native vision (text, image and video)

Kimi K3

Moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores — and its weights are open while GPT-4.1 Mini is API-only.

Vendor reports 81.2 FrontierSWE and 88.3 Terminal-Bench 2.1 on its own harness

Kimi K3

GPT-4.1 Mini is comparatively weak here — weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%

Lowest cost at scale

GPT-4.1 Mini

At $0.4/$1.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Which should you pick?

A cost-sensitive startup shipping high volume

GPT-4.1 Mini

At $0.4/$1.6 per 1M tokens it undercuts Kimi K3, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

Kimi K3

Larger 1M window fits more in one prompt.

A team with data-privacy or self-hosting needs

Kimi K3

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 largest open-weight model at release — 2.8t sparse moe, self-hostable

Kimi K3

That is its strongest area.

An enterprise with regional data-residency rules

GPT-4.1 Mini or Kimi K3

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.

Kimi K3: where it fits

Moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores. Released July 27, 2026 by Moonshot AI, it is built for largest open-weight model at release — 2.8T sparse MoE, self-hostable, 1M-token context with native vision (text, image and video), vendor reports 81.2 FrontierSWE and 88.3 Terminal-Bench 2.1 on its own harness, and fresh-input pricing of $3/M (cached $0.30/M), flat across the full 1M context.

Its trade-offs: coding scores use Moonshot FrontierSWE, not standard SWE-Bench Verified, 2.8T params need serious hardware to self-host — weights are free, running is not, no independent benchmark reproduction yet at release, and image input but no audio or video. At $3 in / $15 out per million tokens, it sits in the mid price band.

The bottom line for this matchup

The defining split here is open vs. closed. Kimi K3 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 Kimi K3 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 GPT-4.1 Mini or Kimi K3 better for coding?

Public SWE-Bench figures are not available for Kimi K3, 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 Kimi K3 leans toward largest open-weight model at release — 2.8t sparse moe, self-hostable, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, GPT-4.1 Mini or Kimi K3?

Kimi K3 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?

Effectively neither — 1M vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both GPT-4.1 Mini and Kimi K3 together?

Yes — a multi-model platform like LumiChats gives you GPT-4.1 Mini, Kimi K3 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 Kimi K3?

Kimi K3 — released July 27, 2026, about 16 months after GPT-4.1 Mini.

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.