Pick Kimi K2.5 for native multimodal reasoning and visual coding or agentic tool-calling and self-directed multi-step work. Pick MiniMax M2.7 for agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported) or independently ranked 14th of 97 on the artificial analysis intelligence index. On a tight budget at scale, MiniMax M2.7 is the value pick.
Kimi K2.5 (Moonshot AI) and MiniMax M2.7 (MiniMax) are two of the models people most often weigh against each other in 2026. 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open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7. MiniMax M2.7 is a cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: MiniMax M2.7 is about 2× cheaper on input ($0.3/$1.2 per 1M tokens vs $0.6/$2.5 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: Kimi K2.5 holds 1.3× more — 256K (~393 pages) vs 205K (~307 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: MiniMax M2.7 is the newer model by about 50 days (released March 18, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Kimi K2.5
MiniMax M2.7
Provider
Moonshot AI (China)
MiniMax (China)
Released
January 27, 2026
March 18, 2026
Context window
256K (~393 pages)
205K (~307 pages)
Price (in/out)
$0.6/$2.5 per 1M tokens
$0.3/$1.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Native multimodal reasoning and visual coding: 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open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7 — and it carries the larger 256K context.
Agentic tool-calling and self-directed multi-step work: Kimi K2.5 — Kimi K2.5 lists agentic tool-calling and self-directed multi-step work among its strengths; MiniMax M2.7 does not.
Open-weight (Modified-MIT) — self-hostable at 256K context: Kimi K2.5 — Its 256K window holds about 1.3× more than MiniMax M2.7's 205K in a single prompt.
Agentic and terminal coding well above its price tier (57.0 on Terminal-Bench 2, vendor-reported): MiniMax M2.7 — At $0.3/$1.2 per 1M tokens it undercuts Kimi K2.5 ($0.6/$2.5 per 1M tokens), and that gap compounds at volume.
Independently ranked 14th of 97 on the Artificial Analysis Intelligence Index: MiniMax M2.7 — A cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks — and it runs cheaper at $0.3/$1.2 per 1M tokens.
Sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware: MiniMax M2.7 — A cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks — and it is the newer of the two.
Lowest cost at scale: MiniMax M2.7 — At $0.3/$1.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Kimi K2.5 — Its 256K window is about 1.3× larger than MiniMax M2.7's 205K, fitting roughly 393 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MiniMax M2.7 — At $0.3/$1.2 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: Kimi K2.5 — Larger 256K window fits more in one prompt.
Anyone whose priority is native multimodal reasoning and visual coding: Kimi K2.5 — It is specifically built for that.
Anyone whose priority is agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported): MiniMax M2.7 — That is its strongest area.
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 are real: 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 $0.6 in / $2.5 out per million tokens, it sits in the budget price band.
MiniMax M2.7: where it fits
A cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks. Released March 18, 2026 by MiniMax, it is built for agentic and terminal coding well above its price tier (57.0 on Terminal-Bench 2, vendor-reported), independently ranked 14th of 97 on the Artificial Analysis Intelligence Index, sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware, and served by five separate hosts at uniform pricing, so there is no provider lock-in.
Its trade-offs: open weights but a NON-COMMERCIAL licence — commercial use requires prior written authorisation from MiniMax, and at least one major tracker still mislabels it as MIT, reports SWE-Bench Pro instead of the standard Verified set, which blocks like-for-like comparison, and already superseded internally by M3, and its 205K context is small against 1M-class rivals. At $0.3 in / $1.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Kimi K2.5 and MiniMax M2.7 overlap enough that the right pick depends on your specific job. MiniMax M2.7 costs less per token; Kimi K2.5 holds the larger context; and each leads in its own area — Kimi K2.5 for native multimodal reasoning and visual coding, MiniMax M2.7 for agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Kimi K2.5 or MiniMax M2.7 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, Kimi K2.5 leans toward native multimodal reasoning and visual coding while MiniMax M2.7 leans toward agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Kimi K2.5 or MiniMax M2.7?
MiniMax M2.7 is cheaper — $0.6/$2.5 per 1M tokens vs $0.3/$1.2 per 1M tokens, roughly 2× apart on input.
Which has the bigger context window?
Kimi K2.5 — 256K vs 205K, about 1.3× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Kimi K2.5 and MiniMax M2.7 together?
Yes — a multi-model platform like LumiChats gives you Kimi K2.5, MiniMax M2.7 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, Kimi K2.5 or MiniMax M2.7?
MiniMax M2.7 — released March 18, 2026, about 50 days after Kimi K2.5.
Kimi K2.5 vs MiniMax M2.7
Moonshot AI · China | MiniMax · China · Updated June 2026
Quick verdict
Pick Kimi K2.5 for native multimodal reasoning and visual coding or agentic tool-calling and self-directed multi-step work. Pick MiniMax M2.7 for agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported) or independently ranked 14th of 97 on the artificial analysis intelligence index. On a tight budget at scale, MiniMax M2.7 is the value pick.
Kimi K2.5 (Moonshot AI) and MiniMax M2.7 (MiniMax) are two of the models people most often weigh against each other in 2026. 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. MiniMax M2.7 is a cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: MiniMax M2.7 is about 2× cheaper on input ($0.3/$1.2 per 1M tokens vs $0.6/$2.5 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: Kimi K2.5 holds 1.3× more — 256K (~393 pages) vs 205K (~307 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: MiniMax M2.7 is the newer model by about 50 days (released March 18, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Kimi K2.5
MiniMax M2.7
Provider
Moonshot AI (China)
MiniMax (China)
Released
January 27, 2026
March 18, 2026
Context window
256K (~393 pages)
205K (~307 pages)
Price (in/out)
$0.6/$2.5 per 1M tokens
$0.3/$1.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Native multimodal reasoning and visual coding
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 it carries the larger 256K context.
Agentic tool-calling and self-directed multi-step work
Kimi K2.5
Kimi K2.5 lists agentic tool-calling and self-directed multi-step work among its strengths; MiniMax M2.7 does not.
Open-weight (Modified-MIT) — self-hostable at 256K context
Kimi K2.5
Its 256K window holds about 1.3× more than MiniMax M2.7's 205K in a single prompt.
Agentic and terminal coding well above its price tier (57.0 on Terminal-Bench 2, vendor-reported)
MiniMax M2.7
At $0.3/$1.2 per 1M tokens it undercuts Kimi K2.5 ($0.6/$2.5 per 1M tokens), and that gap compounds at volume.
Independently ranked 14th of 97 on the Artificial Analysis Intelligence Index
MiniMax M2.7
A cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks — and it runs cheaper at $0.3/$1.2 per 1M tokens.
Sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware
MiniMax M2.7
A cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks — and it is the newer of the two.
Lowest cost at scale
MiniMax M2.7
At $0.3/$1.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Kimi K2.5
Its 256K window is about 1.3× larger than MiniMax M2.7's 205K, fitting roughly 393 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiniMax M2.7
At $0.3/$1.2 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
→ Kimi K2.5
Larger 256K window fits more in one prompt.
Anyone whose priority is native multimodal reasoning and visual coding
→ Kimi K2.5
It is specifically built for that.
Anyone whose priority is agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported)
→ MiniMax M2.7
That is its strongest area.
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 are real: 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 $0.6 in / $2.5 out per million tokens, it sits in the budget price band.
MiniMax M2.7: where it fits
A cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks. Released March 18, 2026 by MiniMax, it is built for agentic and terminal coding well above its price tier (57.0 on Terminal-Bench 2, vendor-reported), independently ranked 14th of 97 on the Artificial Analysis Intelligence Index, sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware, and served by five separate hosts at uniform pricing, so there is no provider lock-in.
Its trade-offs: open weights but a NON-COMMERCIAL licence — commercial use requires prior written authorisation from MiniMax, and at least one major tracker still mislabels it as MIT, reports SWE-Bench Pro instead of the standard Verified set, which blocks like-for-like comparison, and already superseded internally by M3, and its 205K context is small against 1M-class rivals. At $0.3 in / $1.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Kimi K2.5 and MiniMax M2.7 overlap enough that the right pick depends on your specific job. MiniMax M2.7 costs less per token; Kimi K2.5 holds the larger context; and each leads in its own area — Kimi K2.5 for native multimodal reasoning and visual coding, MiniMax M2.7 for agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Kimi K2.5 and MiniMax M2.7 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, Kimi K2.5 leans toward native multimodal reasoning and visual coding while MiniMax M2.7 leans toward agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Kimi K2.5 or MiniMax M2.7?
MiniMax M2.7 is cheaper — $0.6/$2.5 per 1M tokens vs $0.3/$1.2 per 1M tokens, roughly 2× apart on input.
Which has the bigger context window?
Kimi K2.5 — 256K vs 205K, about 1.3× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Kimi K2.5 and MiniMax M2.7 together?
Yes — a multi-model platform like LumiChats gives you Kimi K2.5, MiniMax M2.7 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, Kimi K2.5 or MiniMax M2.7?
MiniMax M2.7 — released March 18, 2026, about 50 days 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.