GPT-6 Astra vs MiniMax M3

OpenAI · US  |  MiniMax · China · Updated June 2026

Quick verdict

Pick GPT-6 Astra for computer & browser use (screenspot-pro 92.7%) or cybersecurity exploit development (exploitbench 100%). 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-6 Astra if you want a managed API.

GPT-6 Astra (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-6 Astra is openAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks. 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

Side-by-side specs

SpecGPT-6 AstraMiniMax M3
ProviderOpenAI (US) MiniMax (China)
ReleasedSeptember 3, 2026 May 31, 2026
Context window1.05M tokens (~1,575 pages) 1M (~1,573 pages)
Price (in/out)$10/$50 per 1M tokens $0.23/$0.96 per 1M tokens
Open weight?No — API only Yes — self-hostable
Modalitiestext, image text, image, video, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1M96.3% Not published

Who wins what

Computer & browser use (ScreenSpot-Pro 92.7%)

GPT-6 Astra

OpenAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks — and it is the newer of the two.

Cybersecurity exploit development (ExploitBench 100%)

GPT-6 Astra

GPT-6 Astra lists cybersecurity exploit development (ExploitBench 100%) among its strengths; MiniMax M3 does not.

Frontier math reasoning (FrontierMath Tier 4: 97.6%)

GPT-6 Astra

GPT-6 Astra lists frontier math reasoning (FrontierMath Tier 4: 97.6%) 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-6 Astra is API-only, so it cannot leave the vendor's servers.

Native multimodal input — text, image and video

MiniMax M3

GPT-6 Astra is comparatively weak here — no native audio or video input

Reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5

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 $0.23/$0.96 per 1M tokens.

Lowest cost at scale

MiniMax M3

At $0.23/$0.96 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 $0.23/$0.96 per 1M tokens it undercuts GPT-6 Astra, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

GPT-6 Astra

Larger 1.05M tokens 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-6 Astra is API-only.

Anyone whose priority is computer & browser use (screenspot-pro 92.7%)

GPT-6 Astra

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-6 Astra 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-6 Astra: where it fits

OpenAI's flagship reasoning model for computer use, browsing, coding and science, released September 3, 2026 with near-perfect scores on FrontierMath, ExploitBench and long-context recall benchmarks. Released September 3, 2026 by OpenAI, it is built for computer & browser use (ScreenSpot-Pro 92.7%), cybersecurity exploit development (ExploitBench 100%), frontier math reasoning (FrontierMath Tier 4: 97.6%), and long-context recall (MRCR v2 512K-1M: 96.3%).

Its trade-offs are real: no native audio or video input, pricing doubles for prompts over 272K tokens (input/cache 2x, output 1.5x), trails Meta's Muse Spark 1.3 on some coding evals (DeepSWE v1.1: 74.1 vs 75.4), and a separate opt-in "Daybreak" program gives vetted cybersecurity defenders a less-restricted version for legitimate vulnerability research; the public version already refuses ~91.5% of offensive cyber jailbreak attempts by default. At $10 in / $50 out per million tokens, it sits in the premium 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 May 31, 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 $0.23 in / $0.96 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-6 Astra 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-6 Astra 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.

See pricing

Frequently asked questions

Is GPT-6 Astra 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-6 Astra leans toward computer & browser use (screenspot-pro 92.7%) 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-6 Astra or MiniMax M3?

MiniMax M3 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-6 Astra is API-metered at $10/$50 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 — 1.05M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both GPT-6 Astra and MiniMax M3 together?

Yes — a multi-model platform like LumiChats gives you GPT-6 Astra, 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-6 Astra or MiniMax M3?

GPT-6 Astra — released September 3, 2026, about 3 months after MiniMax M3.

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.