Pick Claude Haiku 4.5 for fastest claude model or near-frontier coding for its tier — 73.3% on swe-bench verified. 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; Claude Haiku 4.5 if you want a managed API.
Claude Haiku 4.5 (Anthropic) and Inkling (Thinking Machines Lab) are two of the models people most often weigh against each other in 2026. Claude Haiku 4.5 is anthropic's fastest, most compact model — built for speed and volume. 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 Claude Haiku 4.5 is API-metered at $1/$5 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: Inkling holds 5× more — 1M (~1,500 pages) vs 200K (~300 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 9 months (released July 15, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Claude Haiku 4.5
Inkling
Provider
Anthropic (US)
Thinking Machines Lab (US)
Released
October 15, 2025
July 15, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1/$5 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
73.3%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fastest Claude model: Claude Haiku 4.5 — Claude Haiku 4.5 lists fastest Claude model among its strengths; Inkling does not.
Near-frontier coding for its tier — 73.3% on SWE-Bench Verified: Claude Haiku 4.5 — Inkling is comparatively weak here — independent third-party benchmark verification is still limited given how recently it shipped
Low-latency, high-volume API calls: Claude Haiku 4.5 — Claude Haiku 4.5 lists low-latency, high-volume API calls 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 — Claude Haiku 4.5 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 — Claude Haiku 4.5 is comparatively weak here — not for deep reasoning
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 it carries the larger 1M context.
Lowest cost at scale: Inkling — Its weights are open, so at volume you pay for your own hardware instead of Claude Haiku 4.5's $1/$5 per 1M tokens.
Largest single-prompt input: Inkling — Its 1M window is about 5× larger than Claude Haiku 4.5's 200K, 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 Claude Haiku 4.5, 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; Claude Haiku 4.5 is API-only.
Anyone whose priority is fastest claude model: Claude Haiku 4.5 — 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.
Claude Haiku 4.5: where it fits
Anthropic's fastest, most compact model — built for speed and volume. Released October 15, 2025 by Anthropic, it is built for fastest Claude model, near-frontier coding for its tier — 73.3% on SWE-Bench Verified, low-latency, high-volume API calls, and cheapest Claude tier at $1/$5.
Its trade-offs are real: smallest context in the family (200K), and not for deep reasoning. At $1 in / $5 out per million tokens, it sits in the budget 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. Claude Haiku 4.5 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 Claude Haiku 4.5 or Inkling better for coding?
Public SWE-Bench figures are not available for Inkling, so the honest test is your own repository — run an identical real bug through both. By design, Claude Haiku 4.5 leans toward fastest claude model 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, Claude Haiku 4.5 or Inkling?
Inkling is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Haiku 4.5 is API-metered at $1/$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?
Inkling — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Haiku 4.5 and Inkling together?
Yes — a multi-model platform like LumiChats gives you Claude Haiku 4.5, 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, Claude Haiku 4.5 or Inkling?
Inkling — released July 15, 2026, about 9 months after Claude Haiku 4.5.
Claude Haiku 4.5 vs Inkling
Anthropic · US | Thinking Machines Lab · US · Updated June 2026
Quick verdict
Pick Claude Haiku 4.5 for fastest claude model or near-frontier coding for its tier — 73.3% on swe-bench verified. 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; Claude Haiku 4.5 if you want a managed API.
Claude Haiku 4.5 (Anthropic) and Inkling (Thinking Machines Lab) are two of the models people most often weigh against each other in 2026. Claude Haiku 4.5 is anthropic's fastest, most compact model — built for speed and volume. 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 Claude Haiku 4.5 is API-metered at $1/$5 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: Inkling holds 5× more — 1M (~1,500 pages) vs 200K (~300 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 9 months (released July 15, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Claude Haiku 4.5
Inkling
Provider
Anthropic (US)
Thinking Machines Lab (US)
Released
October 15, 2025
July 15, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1/$5 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
73.3%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fastest Claude model
Claude Haiku 4.5
Claude Haiku 4.5 lists fastest Claude model among its strengths; Inkling does not.
Near-frontier coding for its tier — 73.3% on SWE-Bench Verified
Claude Haiku 4.5
Inkling is comparatively weak here — independent third-party benchmark verification is still limited given how recently it shipped
Low-latency, high-volume API calls
Claude Haiku 4.5
Claude Haiku 4.5 lists low-latency, high-volume API calls 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 — Claude Haiku 4.5 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
Claude Haiku 4.5 is comparatively weak here — not for deep reasoning
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 it carries the larger 1M context.
Lowest cost at scale
Inkling
Its weights are open, so at volume you pay for your own hardware instead of Claude Haiku 4.5's $1/$5 per 1M tokens.
Largest single-prompt input
Inkling
Its 1M window is about 5× larger than Claude Haiku 4.5's 200K, 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 Claude Haiku 4.5, 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; Claude Haiku 4.5 is API-only.
Anyone whose priority is fastest claude model
→ Claude Haiku 4.5
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.
Claude Haiku 4.5: where it fits
Anthropic's fastest, most compact model — built for speed and volume. Released October 15, 2025 by Anthropic, it is built for fastest Claude model, near-frontier coding for its tier — 73.3% on SWE-Bench Verified, low-latency, high-volume API calls, and cheapest Claude tier at $1/$5.
Its trade-offs are real: smallest context in the family (200K), and not for deep reasoning. At $1 in / $5 out per million tokens, it sits in the budget 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. Claude Haiku 4.5 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 Claude Haiku 4.5 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 Inkling, so the honest test is your own repository — run an identical real bug through both. By design, Claude Haiku 4.5 leans toward fastest claude model 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, Claude Haiku 4.5 or Inkling?
Inkling is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Haiku 4.5 is API-metered at $1/$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?
Inkling — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Haiku 4.5 and Inkling together?
Yes — a multi-model platform like LumiChats gives you Claude Haiku 4.5, 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, Claude Haiku 4.5 or Inkling?
Inkling — released July 15, 2026, about 9 months after Claude Haiku 4.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.