Pick Inkling for the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai or a 975b-parameter moe (41b active) with native text, image, and audio reasoning in one model. Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). On a tight budget at scale, Inkling is the value pick.
Inkling (Thinking Machines Lab, 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. Inkling is mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: Inkling is the newer model by about 3 months (released July 15, 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
Inkling
MiMo-V2.5
Provider
Thinking Machines Lab (US)
Xiaomi (China)
Released
July 15, 2026
April 22, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
Open weight (self-host / free)
$0.14/$0.28 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, audio, code
text, image, audio, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
The first model release from Mira Murati's Thinking Machines Lab (ex-OpenAI CTO) - one of the most closely-watched new labs in AI: Inkling — Mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control — and it is the newer of the two.
A 975B-parameter MoE (41B active) with native text, image, and audio reasoning in one model: Inkling — MiMo-V2.5 is comparatively weak here — not the deepest reasoning tier (see V2.5-Pro)
A dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request: Inkling — Inkling lists a dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request among its strengths; MiMo-V2.5 does not.
Native omnimodal — strong image and video understanding: MiMo-V2.5 — MiMo-V2.5 lists native omnimodal — strong image and video understanding among its strengths; Inkling does not.
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; Inkling does not.
Agent-framework integration: MiMo-V2.5 — MiMo-V2.5 lists agent-framework integration among its strengths; Inkling does not.
Lowest cost at scale: Inkling — Its weights are open, so at volume you pay for your own hardware instead of MiMo-V2.5's $0.14/$0.28 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Inkling — At Open weight (self-host / free) it undercuts MiMo-V2.5, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai: Inkling — 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: Inkling 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.
Inkling: where it fits
Mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control. Released July 15, 2026 by Thinking Machines Lab, it is built for the first model release from Mira Murati's Thinking Machines Lab (ex-OpenAI CTO) - one of the most closely-watched new labs in AI, a 975B-parameter MoE (41B active) with native text, image, and audio reasoning in one model, a dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request, and fully open weights (Apache 2.0) at frontier scale - unusual for a model this large and this new.
Its trade-offs are real: a brand-new lab's first release - no multi-generation track record yet, no official hosted API price - available via third-party hosts only at launch, and independent third-party benchmark verification is still limited given how recently it shipped. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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
This is less "which is smarter" and more "which ecosystem fits." Inkling (US) and MiMo-V2.5 (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Inkling is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Frequently asked questions
Is Inkling 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, Inkling leans toward the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai 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, Inkling or MiMo-V2.5?
Inkling is cheaper — Open weight (self-host / free) vs $0.14/$0.28 per 1M tokens.
Which has the bigger context window?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Inkling and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you Inkling, 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, Inkling or MiMo-V2.5?
Inkling — released July 15, 2026, about 3 months after MiMo-V2.5.
Inkling vs MiMo-V2.5
Thinking Machines Lab · US | Xiaomi · China · Updated June 2026
Quick verdict
Pick Inkling for the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai or a 975b-parameter moe (41b active) with native text, image, and audio reasoning in one model. Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). On a tight budget at scale, Inkling is the value pick.
Inkling (Thinking Machines Lab, 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. Inkling is mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: Inkling is the newer model by about 3 months (released July 15, 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
Inkling
MiMo-V2.5
Provider
Thinking Machines Lab (US)
Xiaomi (China)
Released
July 15, 2026
April 22, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
Open weight (self-host / free)
$0.14/$0.28 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, audio, code
text, image, audio, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
The first model release from Mira Murati's Thinking Machines Lab (ex-OpenAI CTO) - one of the most closely-watched new labs in AI
Inkling
Mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control — and it is the newer of the two.
A 975B-parameter MoE (41B active) with native text, image, and audio reasoning in one model
Inkling
MiMo-V2.5 is comparatively weak here — not the deepest reasoning tier (see V2.5-Pro)
A dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request
Inkling
Inkling lists a dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request among its strengths; MiMo-V2.5 does not.
Native omnimodal — strong image and video understanding
MiMo-V2.5
MiMo-V2.5 lists native omnimodal — strong image and video understanding among its strengths; Inkling does not.
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; Inkling does not.
Agent-framework integration
MiMo-V2.5
MiMo-V2.5 lists agent-framework integration among its strengths; Inkling does not.
Lowest cost at scale
Inkling
Its weights are open, so at volume you pay for your own hardware instead of MiMo-V2.5's $0.14/$0.28 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Inkling
At Open weight (self-host / free) it undercuts MiMo-V2.5, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai
→ Inkling
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
→ Inkling 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.
Inkling: where it fits
Mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control. Released July 15, 2026 by Thinking Machines Lab, it is built for the first model release from Mira Murati's Thinking Machines Lab (ex-OpenAI CTO) - one of the most closely-watched new labs in AI, a 975B-parameter MoE (41B active) with native text, image, and audio reasoning in one model, a dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request, and fully open weights (Apache 2.0) at frontier scale - unusual for a model this large and this new.
Its trade-offs are real: a brand-new lab's first release - no multi-generation track record yet, no official hosted API price - available via third-party hosts only at launch, and independent third-party benchmark verification is still limited given how recently it shipped. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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
This is less "which is smarter" and more "which ecosystem fits." Inkling (US) and MiMo-V2.5 (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Inkling is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both Inkling 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, Inkling leans toward the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai 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, Inkling or MiMo-V2.5?
Inkling is cheaper — Open weight (self-host / free) vs $0.14/$0.28 per 1M tokens.
Which has the bigger context window?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Inkling and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you Inkling, 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, Inkling or MiMo-V2.5?
Inkling — released July 15, 2026, about 3 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.