Pick GPT-6 Luna for openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume or available to free and go plan users in the chatgpt desktop app, not gated to paid tiers. 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 Luna if you want a managed API.
GPT-6 Luna (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 Luna is openAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth. 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: GPT-6 Luna is about 1.4× cheaper on input ($0.1/$0.5 per 1M tokens vs $0.14/$0.28 per 1M tokens) — modest, but it adds up at steady volume.
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 Luna is the newer model by about 5 months (released September 22, 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 Luna
MiMo-V2.5
Provider
OpenAI (US)
Xiaomi (China)
Released
September 22, 2026
April 22, 2026
Context window
1.05M tokens (~1,575 pages)
1M (~1,500 pages)
Price (in/out)
$0.1/$0.5 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
Not published
Not published
Who wins what
OpenAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume: GPT-6 Luna — At $0.1/$0.5 per 1M tokens it undercuts MiMo-V2.5 ($0.14/$0.28 per 1M tokens), and that gap compounds at volume.
Available to Free and Go plan users in the ChatGPT desktop app, not gated to paid tiers: GPT-6 Luna — OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth — and it runs cheaper at $0.1/$0.5 per 1M tokens.
Cache reads at $0.01/MTok — a 90% discount, the cheapest in the GPT-6 family: GPT-6 Luna — OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth — and it is the newer of the two.
Native omnimodal — strong image and video understanding: MiMo-V2.5 — Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost — and its weights are open while GPT-6 Luna is API-only.
Very low cost (~half the inference of the Pro tier): MiMo-V2.5 — MiMo-V2.5 lists very low cost (~half the inference of the Pro tier) among its strengths; GPT-6 Luna does not.
Agent-framework integration: MiMo-V2.5 — MiMo-V2.5 lists agent-framework integration among its strengths; GPT-6 Luna does not.
Lowest cost at scale: GPT-6 Luna — At $0.1/$0.5 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-6 Luna — At $0.1/$0.5 per 1M tokens it undercuts MiMo-V2.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-6 Luna — 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 Luna is API-only.
Anyone whose priority is openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume: GPT-6 Luna — 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 Luna 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 Luna: where it fits
OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth. Released September 22, 2026 by OpenAI, it is built for openAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume, available to Free and Go plan users in the ChatGPT desktop app, not gated to paid tiers, cache reads at $0.01/MTok — a 90% discount, the cheapest in the GPT-6 family, and 1.05M-token context window carried down from the flagship tier.
Its trade-offs are real: less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems, and as the entry-level tier, expect it to be the first model swapped out when OpenAI ships the next cost-tier refresh. At $0.1 in / $0.5 out per million tokens, it sits in the budget 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 Luna 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 Luna 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 Luna leans toward openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume 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 Luna 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 Luna is API-metered at $0.1/$0.5 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 Luna and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Luna, 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 Luna or MiMo-V2.5?
GPT-6 Luna — released September 22, 2026, about 5 months after MiMo-V2.5.
GPT-6 Luna vs MiMo-V2.5
OpenAI · US | Xiaomi · China · Updated June 2026
Quick verdict
Pick GPT-6 Luna for openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume or available to free and go plan users in the chatgpt desktop app, not gated to paid tiers. 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 Luna if you want a managed API.
GPT-6 Luna (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 Luna is openAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth. 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: GPT-6 Luna is about 1.4× cheaper on input ($0.1/$0.5 per 1M tokens vs $0.14/$0.28 per 1M tokens) — modest, but it adds up at steady volume.
▸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 Luna is the newer model by about 5 months (released September 22, 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 Luna
MiMo-V2.5
Provider
OpenAI (US)
Xiaomi (China)
Released
September 22, 2026
April 22, 2026
Context window
1.05M tokens (~1,575 pages)
1M (~1,500 pages)
Price (in/out)
$0.1/$0.5 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
Not published
Not published
Who wins what
OpenAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume
GPT-6 Luna
At $0.1/$0.5 per 1M tokens it undercuts MiMo-V2.5 ($0.14/$0.28 per 1M tokens), and that gap compounds at volume.
Available to Free and Go plan users in the ChatGPT desktop app, not gated to paid tiers
GPT-6 Luna
OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth — and it runs cheaper at $0.1/$0.5 per 1M tokens.
Cache reads at $0.01/MTok — a 90% discount, the cheapest in the GPT-6 family
GPT-6 Luna
OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth — and it is the newer of the two.
Native omnimodal — strong image and video understanding
MiMo-V2.5
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost — and its weights are open while GPT-6 Luna is API-only.
Very low cost (~half the inference of the Pro tier)
MiMo-V2.5
MiMo-V2.5 lists very low cost (~half the inference of the Pro tier) among its strengths; GPT-6 Luna does not.
Agent-framework integration
MiMo-V2.5
MiMo-V2.5 lists agent-framework integration among its strengths; GPT-6 Luna does not.
Lowest cost at scale
GPT-6 Luna
At $0.1/$0.5 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-6 Luna
At $0.1/$0.5 per 1M tokens it undercuts MiMo-V2.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-6 Luna
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 Luna is API-only.
Anyone whose priority is openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume
→ GPT-6 Luna
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 Luna 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 Luna: where it fits
OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth. Released September 22, 2026 by OpenAI, it is built for openAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume, available to Free and Go plan users in the ChatGPT desktop app, not gated to paid tiers, cache reads at $0.01/MTok — a 90% discount, the cheapest in the GPT-6 family, and 1.05M-token context window carried down from the flagship tier.
Its trade-offs are real: less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems, and as the entry-level tier, expect it to be the first model swapped out when OpenAI ships the next cost-tier refresh. At $0.1 in / $0.5 out per million tokens, it sits in the budget 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 Luna 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 Luna 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 Luna leans toward openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume 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 Luna 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 Luna is API-metered at $0.1/$0.5 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 Luna and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Luna, 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 Luna or MiMo-V2.5?
GPT-6 Luna — released September 22, 2026, about 5 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.