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 Kimi K2.5 for native multimodal reasoning and visual coding or agentic tool-calling and self-directed multi-step work. Choose Kimi K2.5 if you need self-hosting or data privacy; GPT-6 Luna if you want a managed API.
GPT-6 Luna (OpenAI, US) and Kimi K2.5 (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-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. Kimi K2.5 is moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7. 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 4.5× cheaper on input ($0.1/$0.5 per 1M tokens vs $0.45/$2.25 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: GPT-6 Luna holds 4× more — 1.05M tokens (~1,575 pages) vs 256K (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: GPT-6 Luna is the newer model by about 8 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
Kimi K2.5
Provider
OpenAI (US)
Moonshot AI (China)
Released
September 22, 2026
January 27, 2026
Context window
1.05M tokens (~1,575 pages)
256K (~393 pages)
Price (in/out)
$0.1/$0.5 per 1M tokens
$0.45/$2.25 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, image, 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 Kimi K2.5 ($0.45/$2.25 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 carries the larger 1.05M tokens context.
Native multimodal reasoning and visual coding: Kimi K2.5 — GPT-6 Luna is comparatively weak here — less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems
Agentic tool-calling and self-directed multi-step work: Kimi K2.5 — Moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7 — and its weights are open while GPT-6 Luna is API-only.
Open-weight (Modified-MIT) — self-hostable at 256K context: Kimi K2.5 — Open weights make this possible at all — GPT-6 Luna is API-only, so it cannot leave the vendor's servers.
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.
Largest single-prompt input: GPT-6 Luna — Its 1.05M tokens window is about 4× larger than Kimi K2.5's 256K, fitting roughly 1,575 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-6 Luna — At $0.1/$0.5 per 1M tokens it undercuts Kimi K2.5, 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: Kimi K2.5 — 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 multimodal reasoning and visual coding: Kimi K2.5 — That is its strongest area.
An enterprise with regional data-residency rules: GPT-6 Luna or Kimi K2.5 — 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.
Kimi K2.5: where it fits
Moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7. Released January 27, 2026 by Moonshot AI, it is built for native multimodal reasoning and visual coding, agentic tool-calling and self-directed multi-step work, open-weight (Modified-MIT) — self-hostable at 256K context, and vendor reports around 76.8% on its own SWE-agent coding harness.
Its trade-offs: its coding score uses Moonshot's own harness, not the standard SWE-Bench Verified protocol, superseded within Moonshot's line by Kimi K2.6 and K2.7, openRouter shows a promo price below Moonshot's $0.60/$2.50 list, and image input but no audio or video. At $0.45 in / $2.25 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. Kimi K2.5 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 Kimi K2.5 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 Kimi K2.5 leans toward native multimodal reasoning and visual coding, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6 Luna or Kimi K2.5?
Kimi K2.5 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?
GPT-6 Luna — 1.05M tokens vs 256K, about 4× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-6 Luna and Kimi K2.5 together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Luna, Kimi K2.5 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 Kimi K2.5?
GPT-6 Luna — released September 22, 2026, about 8 months after Kimi K2.5.
GPT-6 Luna vs Kimi K2.5
OpenAI · US | Moonshot AI · 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 Kimi K2.5 for native multimodal reasoning and visual coding or agentic tool-calling and self-directed multi-step work. Choose Kimi K2.5 if you need self-hosting or data privacy; GPT-6 Luna if you want a managed API.
GPT-6 Luna (OpenAI, US) and Kimi K2.5 (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-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. Kimi K2.5 is moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7. 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 4.5× cheaper on input ($0.1/$0.5 per 1M tokens vs $0.45/$2.25 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: GPT-6 Luna holds 4× more — 1.05M tokens (~1,575 pages) vs 256K (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: GPT-6 Luna is the newer model by about 8 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
Kimi K2.5
Provider
OpenAI (US)
Moonshot AI (China)
Released
September 22, 2026
January 27, 2026
Context window
1.05M tokens (~1,575 pages)
256K (~393 pages)
Price (in/out)
$0.1/$0.5 per 1M tokens
$0.45/$2.25 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, image, 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 Kimi K2.5 ($0.45/$2.25 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 carries the larger 1.05M tokens context.
Native multimodal reasoning and visual coding
Kimi K2.5
GPT-6 Luna is comparatively weak here — less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems
Agentic tool-calling and self-directed multi-step work
Kimi K2.5
Moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7 — and its weights are open while GPT-6 Luna is API-only.
Open-weight (Modified-MIT) — self-hostable at 256K context
Kimi K2.5
Open weights make this possible at all — GPT-6 Luna is API-only, so it cannot leave the vendor's servers.
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.
Largest single-prompt input
GPT-6 Luna
Its 1.05M tokens window is about 4× larger than Kimi K2.5's 256K, fitting roughly 1,575 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-6 Luna
At $0.1/$0.5 per 1M tokens it undercuts Kimi K2.5, 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
→ Kimi K2.5
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 multimodal reasoning and visual coding
→ Kimi K2.5
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-6 Luna or Kimi K2.5
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.
Kimi K2.5: where it fits
Moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7. Released January 27, 2026 by Moonshot AI, it is built for native multimodal reasoning and visual coding, agentic tool-calling and self-directed multi-step work, open-weight (Modified-MIT) — self-hostable at 256K context, and vendor reports around 76.8% on its own SWE-agent coding harness.
Its trade-offs: its coding score uses Moonshot's own harness, not the standard SWE-Bench Verified protocol, superseded within Moonshot's line by Kimi K2.6 and K2.7, openRouter shows a promo price below Moonshot's $0.60/$2.50 list, and image input but no audio or video. At $0.45 in / $2.25 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. Kimi K2.5 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 Kimi K2.5 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 Kimi K2.5 leans toward native multimodal reasoning and visual coding, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6 Luna or Kimi K2.5?
Kimi K2.5 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?
GPT-6 Luna — 1.05M tokens vs 256K, about 4× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-6 Luna and Kimi K2.5 together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Luna, Kimi K2.5 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 Kimi K2.5?
GPT-6 Luna — released September 22, 2026, about 8 months after Kimi K2.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.