Pick GPT-5.4 for strong general-purpose default or coding and software engineering. Pick MiniMax M3 for open-weight 428b moe (~23b active per token) with a 1m-token context or native multimodal input — text, image and video. Choose MiniMax M3 if you need self-hosting or data privacy; GPT-5.4 if you want a managed API.
GPT-5.4 (OpenAI, US) and MiniMax M3 (MiniMax, 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 is openAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. MiniMax M3 is miniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: MiniMax M3 is about 8.3× cheaper on input ($0.3/$1.2 per 1M tokens vs $2.5/$15 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: 1M vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: MiniMax M3 is the newer model by about 3 months (released June 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
MiniMax M3
Provider
OpenAI (US)
MiniMax (China)
Released
March 5, 2026
June 2026
Context window
1M (~1,500 pages)
1M (~1,573 pages)
Price (in/out)
$2.5/$15 per 1M tokens
$0.3/$1.2 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong general-purpose default: GPT-5.4 — GPT-5.4 lists strong general-purpose default among its strengths; MiniMax M3 does not.
Coding and software engineering: GPT-5.4 — GPT-5.4 lists coding and software engineering among its strengths; MiniMax M3 does not.
Document understanding and tool use: GPT-5.4 — GPT-5.4 lists document understanding and tool use among its strengths; MiniMax M3 does not.
Open-weight 428B MoE (~23B active per token) with a 1M-token context: MiniMax M3 — Open weights make this possible at all — GPT-5.4 is API-only, so it cannot leave the vendor's servers.
Native multimodal input — text, image and video: MiniMax M3 — MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing — and it runs cheaper at $0.3/$1.2 per 1M tokens.
Reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5: MiniMax M3 — GPT-5.4 is comparatively weak here — pricier than open-weight rivals
Lowest cost at scale: MiniMax M3 — At $0.3/$1.2 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: MiniMax M3 — At $0.3/$1.2 per 1M tokens it undercuts GPT-5.4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: MiniMax M3 — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: MiniMax M3 — Open weights let you run it on your own hardware; GPT-5.4 is API-only.
Anyone whose priority is strong general-purpose default: GPT-5.4 — It is specifically built for that.
Anyone whose priority is open-weight 428b moe (~23b active per token) with a 1m-token context: MiniMax M3 — That is its strongest area.
An enterprise with regional data-residency rules: GPT-5.4 or MiniMax M3 — 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: where it fits
OpenAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. Released March 5, 2026 by OpenAI, it is built for strong general-purpose default, coding and software engineering, document understanding and tool use, and 1M context with good token efficiency.
Its trade-offs are real: topped by GPT-5.5 on the hardest tasks, and pricier than open-weight rivals. At $2.5 in / $15 out per million tokens, it sits in the mid price band.
MiniMax M3: where it fits
MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. Released June 2026 by MiniMax, it is built for open-weight 428B MoE (~23B active per token) with a 1M-token context, native multimodal input — text, image and video, reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5, and low entry pricing at $0.30/$1.20 per million up to 512K tokens.
Its trade-offs: price doubles to $0.60/$2.40 above 512K tokens — not flat across 1M, miniMax's own reported 80.5 SWE-Bench Verified figure is vendor-stated, not independently verified, sWE-Bench Pro is a different, harder benchmark than SWE-Bench Verified, and newer than M2.7 but with less independent testing so far. At $0.3 in / $1.2 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. MiniMax M3 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.4 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 or MiniMax M3 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 leans toward strong general-purpose default while MiniMax M3 leans toward open-weight 428b moe (~23b active per token) with a 1m-token context, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 or MiniMax M3?
MiniMax M3 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.4 is API-metered at $2.5/$15 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-5.4 and MiniMax M3 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.4, MiniMax M3 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 or MiniMax M3?
MiniMax M3 — released June 2026, about 3 months after GPT-5.4.
GPT-5.4 vs MiniMax M3
OpenAI · US | MiniMax · China · Updated June 2026
Quick verdict
Pick GPT-5.4 for strong general-purpose default or coding and software engineering. Pick MiniMax M3 for open-weight 428b moe (~23b active per token) with a 1m-token context or native multimodal input — text, image and video. Choose MiniMax M3 if you need self-hosting or data privacy; GPT-5.4 if you want a managed API.
GPT-5.4 (OpenAI, US) and MiniMax M3 (MiniMax, 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 is openAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. MiniMax M3 is miniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. 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: MiniMax M3 is about 8.3× cheaper on input ($0.3/$1.2 per 1M tokens vs $2.5/$15 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: 1M vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: MiniMax M3 is the newer model by about 3 months (released June 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
MiniMax M3
Provider
OpenAI (US)
MiniMax (China)
Released
March 5, 2026
June 2026
Context window
1M (~1,500 pages)
1M (~1,573 pages)
Price (in/out)
$2.5/$15 per 1M tokens
$0.3/$1.2 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong general-purpose default
GPT-5.4
GPT-5.4 lists strong general-purpose default among its strengths; MiniMax M3 does not.
Coding and software engineering
GPT-5.4
GPT-5.4 lists coding and software engineering among its strengths; MiniMax M3 does not.
Document understanding and tool use
GPT-5.4
GPT-5.4 lists document understanding and tool use among its strengths; MiniMax M3 does not.
Open-weight 428B MoE (~23B active per token) with a 1M-token context
MiniMax M3
Open weights make this possible at all — GPT-5.4 is API-only, so it cannot leave the vendor's servers.
Native multimodal input — text, image and video
MiniMax M3
MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing — and it runs cheaper at $0.3/$1.2 per 1M tokens.
Reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5
MiniMax M3
GPT-5.4 is comparatively weak here — pricier than open-weight rivals
Lowest cost at scale
MiniMax M3
At $0.3/$1.2 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
→ MiniMax M3
At $0.3/$1.2 per 1M tokens it undercuts GPT-5.4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ MiniMax M3
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ MiniMax M3
Open weights let you run it on your own hardware; GPT-5.4 is API-only.
Anyone whose priority is strong general-purpose default
→ GPT-5.4
It is specifically built for that.
Anyone whose priority is open-weight 428b moe (~23b active per token) with a 1m-token context
→ MiniMax M3
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-5.4 or MiniMax M3
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: where it fits
OpenAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. Released March 5, 2026 by OpenAI, it is built for strong general-purpose default, coding and software engineering, document understanding and tool use, and 1M context with good token efficiency.
Its trade-offs are real: topped by GPT-5.5 on the hardest tasks, and pricier than open-weight rivals. At $2.5 in / $15 out per million tokens, it sits in the mid price band.
MiniMax M3: where it fits
MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. Released June 2026 by MiniMax, it is built for open-weight 428B MoE (~23B active per token) with a 1M-token context, native multimodal input — text, image and video, reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5, and low entry pricing at $0.30/$1.20 per million up to 512K tokens.
Its trade-offs: price doubles to $0.60/$2.40 above 512K tokens — not flat across 1M, miniMax's own reported 80.5 SWE-Bench Verified figure is vendor-stated, not independently verified, sWE-Bench Pro is a different, harder benchmark than SWE-Bench Verified, and newer than M2.7 but with less independent testing so far. At $0.3 in / $1.2 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. MiniMax M3 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.4 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 and MiniMax M3 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 either model, so the honest test is your own repository — run an identical real bug through both. By design, GPT-5.4 leans toward strong general-purpose default while MiniMax M3 leans toward open-weight 428b moe (~23b active per token) with a 1m-token context, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 or MiniMax M3?
MiniMax M3 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.4 is API-metered at $2.5/$15 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-5.4 and MiniMax M3 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.4, MiniMax M3 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 or MiniMax M3?
MiniMax M3 — released June 2026, about 3 months after GPT-5.4.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.