Pick GPT-6 Astra for computer & browser use (screenspot-pro 92.7%) or cybersecurity exploit development (exploitbench 100%). Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). Choose MiMo-V2.5 if you need self-hosting or data privacy; GPT-6 Astra if you want a managed API.
GPT-6 Astra (OpenAI, US) and MiMo-V2.5 (Xiaomi, 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. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: MiMo-V2.5 is about 71× cheaper on input ($0.14/$0.28 per 1M tokens vs $10/$50 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: 1.05M tokens 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: GPT-6 Astra is the newer model by about 4 months (released September 3, 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-6 Astra
MiMo-V2.5
Provider
OpenAI (US)
Xiaomi (China)
Released
September 3, 2026
April 22, 2026
Context window
1.05M tokens (~1,575 pages)
1M (~1,500 pages)
Price (in/out)
$10/$50 per 1M tokens
$0.14/$0.28 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, image, audio, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
96.3%
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; MiMo-V2.5 does not.
Frontier math reasoning (FrontierMath Tier 4: 97.6%): GPT-6 Astra — MiMo-V2.5 is comparatively weak here — not the deepest reasoning tier (see V2.5-Pro)
Native omnimodal — strong image and video understanding: MiMo-V2.5 — GPT-6 Astra is comparatively weak here — no native audio or video input
Very low cost (~half the inference of the Pro tier): MiMo-V2.5 — At $0.14/$0.28 per 1M tokens it undercuts GPT-6 Astra ($10/$50 per 1M tokens), and that gap compounds at volume.
Agent-framework integration: MiMo-V2.5 — Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost — and it runs cheaper at $0.14/$0.28 per 1M tokens.
Lowest cost at scale: MiMo-V2.5 — At $0.14/$0.28 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: MiMo-V2.5 — At $0.14/$0.28 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: MiMo-V2.5 — 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 native omnimodal — strong image and video understanding: MiMo-V2.5 — That is its strongest area.
An enterprise with regional data-residency rules: GPT-6 Astra or MiMo-V2.5 — 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.
MiMo-V2.5: where it fits
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Released April 22, 2026 by Xiaomi, it is built for native omnimodal — strong image and video understanding, very low cost (~half the inference of the Pro tier), agent-framework integration, and 1M context for full documents in one pass.
Its trade-offs: not the deepest reasoning tier (see V2.5-Pro), and limited Western tooling and support. At $0.14 in / $0.28 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. MiMo-V2.5 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.
Frequently asked questions
Is GPT-6 Astra or MiMo-V2.5 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 MiMo-V2.5 leans toward native omnimodal — strong image and video understanding, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6 Astra or MiMo-V2.5?
MiMo-V2.5 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 MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Astra, MiMo-V2.5 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 MiMo-V2.5?
GPT-6 Astra — released September 3, 2026, about 4 months after MiMo-V2.5.
GPT-6 Astra vs MiMo-V2.5
OpenAI · US | Xiaomi · 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 MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). Choose MiMo-V2.5 if you need self-hosting or data privacy; GPT-6 Astra if you want a managed API.
GPT-6 Astra (OpenAI, US) and MiMo-V2.5 (Xiaomi, 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. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the 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
▸Price: MiMo-V2.5 is about 71× cheaper on input ($0.14/$0.28 per 1M tokens vs $10/$50 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: 1.05M tokens 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: GPT-6 Astra is the newer model by about 4 months (released September 3, 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-6 Astra
MiMo-V2.5
Provider
OpenAI (US)
Xiaomi (China)
Released
September 3, 2026
April 22, 2026
Context window
1.05M tokens (~1,575 pages)
1M (~1,500 pages)
Price (in/out)
$10/$50 per 1M tokens
$0.14/$0.28 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, image, audio, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
96.3%
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; MiMo-V2.5 does not.
Frontier math reasoning (FrontierMath Tier 4: 97.6%)
GPT-6 Astra
MiMo-V2.5 is comparatively weak here — not the deepest reasoning tier (see V2.5-Pro)
Native omnimodal — strong image and video understanding
MiMo-V2.5
GPT-6 Astra is comparatively weak here — no native audio or video input
Very low cost (~half the inference of the Pro tier)
MiMo-V2.5
At $0.14/$0.28 per 1M tokens it undercuts GPT-6 Astra ($10/$50 per 1M tokens), and that gap compounds at volume.
Agent-framework integration
MiMo-V2.5
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost — and it runs cheaper at $0.14/$0.28 per 1M tokens.
Lowest cost at scale
MiMo-V2.5
At $0.14/$0.28 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
→ MiMo-V2.5
At $0.14/$0.28 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
→ MiMo-V2.5
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 native omnimodal — strong image and video understanding
→ MiMo-V2.5
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-6 Astra or MiMo-V2.5
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.
MiMo-V2.5: where it fits
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Released April 22, 2026 by Xiaomi, it is built for native omnimodal — strong image and video understanding, very low cost (~half the inference of the Pro tier), agent-framework integration, and 1M context for full documents in one pass.
Its trade-offs: not the deepest reasoning tier (see V2.5-Pro), and limited Western tooling and support. At $0.14 in / $0.28 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. MiMo-V2.5 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 MiMo-V2.5 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-6 Astra leans toward computer & browser use (screenspot-pro 92.7%) while MiMo-V2.5 leans toward native omnimodal — strong image and video understanding, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6 Astra or MiMo-V2.5?
MiMo-V2.5 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 MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Astra, MiMo-V2.5 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 MiMo-V2.5?
GPT-6 Astra — released September 3, 2026, about 4 months after MiMo-V2.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.