Pick GPT-5.2 for strong all-round reasoning or reliable structured output. 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. Choose Inkling if you need self-hosting or data privacy; GPT-5.2 if you want a managed API.
GPT-5.2 (OpenAI) and Inkling (Thinking Machines Lab) are two of the models people most often weigh against each other in 2026. GPT-5.2 is a capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. 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. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Inkling ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-5.2 is API-metered at $1.75/$14 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: Inkling holds 2.5× more — 1M (~1,500 pages) vs 400K (~600 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Inkling is the newer model by about 7 months (released July 15, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-5.2
Inkling
Provider
OpenAI (US)
Thinking Machines Lab (US)
Released
December 11, 2025
July 15, 2026
Context window
400K (~600 pages)
1M (~1,500 pages)
Price (in/out)
$1.75/$14 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, image, audio, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong all-round reasoning: GPT-5.2 — GPT-5.2 lists strong all-round reasoning among its strengths; Inkling does not.
Reliable structured output: GPT-5.2 — GPT-5.2 lists reliable structured output among its strengths; Inkling does not.
Broad ecosystem and tooling: GPT-5.2 — GPT-5.2 lists broad ecosystem and tooling among its strengths; Inkling does not.
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 — Open weights make this possible at all — GPT-5.2 is API-only, so it cannot leave the vendor's servers.
A 975B-parameter MoE (41B active) with native text, image, and audio reasoning in one model: 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 carries the larger 1M context.
A dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request: 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 its weights are open while GPT-5.2 is API-only.
Lowest cost at scale: Inkling — Its weights are open, so at volume you pay for your own hardware instead of GPT-5.2's $1.75/$14 per 1M tokens.
Largest single-prompt input: Inkling — Its 1M window is about 2.5× larger than GPT-5.2's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Inkling — At Open weight (self-host / free) it undercuts GPT-5.2, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Inkling — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: Inkling — Open weights let you run it on your own hardware; GPT-5.2 is API-only.
Anyone whose priority is strong all-round reasoning: GPT-5.2 — It is specifically built for that.
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 — That is its strongest area.
GPT-5.2: where it fits
A capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. Released December 11, 2025 by OpenAI, it is built for strong all-round reasoning, reliable structured output, broad ecosystem and tooling, and professional workflows.
Its trade-offs are real: superseded by GPT-5.5, and smaller context than flagships. At $1.75 in / $14 out per million tokens, it sits in the mid price band.
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: 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.
The bottom line for this matchup
The defining split here is open vs. closed. Inkling gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.2 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-5.2 or Inkling 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-5.2 leans toward strong all-round reasoning while 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, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.2 or Inkling?
Inkling is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.2 is API-metered at $1.75/$14 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?
Inkling — 1M vs 400K, about 2.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.2 and Inkling together?
Yes — a multi-model platform like LumiChats gives you GPT-5.2, Inkling 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-5.2 or Inkling?
Inkling — released July 15, 2026, about 7 months after GPT-5.2.
GPT-5.2 vs Inkling
OpenAI · US | Thinking Machines Lab · US · Updated June 2026
Quick verdict
Pick GPT-5.2 for strong all-round reasoning or reliable structured output. 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. Choose Inkling if you need self-hosting or data privacy; GPT-5.2 if you want a managed API.
GPT-5.2 (OpenAI) and Inkling (Thinking Machines Lab) are two of the models people most often weigh against each other in 2026. GPT-5.2 is a capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. 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. 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
▸Cost model: Inkling ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-5.2 is API-metered at $1.75/$14 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: Inkling holds 2.5× more — 1M (~1,500 pages) vs 400K (~600 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Inkling is the newer model by about 7 months (released July 15, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-5.2
Inkling
Provider
OpenAI (US)
Thinking Machines Lab (US)
Released
December 11, 2025
July 15, 2026
Context window
400K (~600 pages)
1M (~1,500 pages)
Price (in/out)
$1.75/$14 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, image, audio, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong all-round reasoning
GPT-5.2
GPT-5.2 lists strong all-round reasoning among its strengths; Inkling does not.
Reliable structured output
GPT-5.2
GPT-5.2 lists reliable structured output among its strengths; Inkling does not.
Broad ecosystem and tooling
GPT-5.2
GPT-5.2 lists broad ecosystem and tooling among its strengths; Inkling does not.
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
Open weights make this possible at all — GPT-5.2 is API-only, so it cannot leave the vendor's servers.
A 975B-parameter MoE (41B active) with native text, image, and audio reasoning in one model
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 carries the larger 1M context.
A dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request
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 its weights are open while GPT-5.2 is API-only.
Lowest cost at scale
Inkling
Its weights are open, so at volume you pay for your own hardware instead of GPT-5.2's $1.75/$14 per 1M tokens.
Largest single-prompt input
Inkling
Its 1M window is about 2.5× larger than GPT-5.2's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Inkling
At Open weight (self-host / free) it undercuts GPT-5.2, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Inkling
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Inkling
Open weights let you run it on your own hardware; GPT-5.2 is API-only.
Anyone whose priority is strong all-round reasoning
→ GPT-5.2
It is specifically built for that.
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
That is its strongest area.
GPT-5.2: where it fits
A capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. Released December 11, 2025 by OpenAI, it is built for strong all-round reasoning, reliable structured output, broad ecosystem and tooling, and professional workflows.
Its trade-offs are real: superseded by GPT-5.5, and smaller context than flagships. At $1.75 in / $14 out per million tokens, it sits in the mid price band.
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: 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.
The bottom line for this matchup
The defining split here is open vs. closed. Inkling gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.2 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-5.2 and Inkling 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-5.2 leans toward strong all-round reasoning while 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, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.2 or Inkling?
Inkling is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.2 is API-metered at $1.75/$14 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?
Inkling — 1M vs 400K, about 2.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.2 and Inkling together?
Yes — a multi-model platform like LumiChats gives you GPT-5.2, Inkling 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-5.2 or Inkling?
Inkling — released July 15, 2026, about 7 months after GPT-5.2.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.