GPT-6.1 Sol vs OLMo 3 32B Think
OpenAI · US | Allen Institute for AI · US · Updated June 2026
Quick verdict
Pick GPT-6.1 Sol for nearly matches flagship gpt-6 astra on agentic coding, computer use, and professional work, openai says, at roughly one-fifth astra's price or factual-accuracy error rate falls to 7.7% at low reasoning effort, down from gpt-6 sol's 11.4%. Pick OLMo 3 32B Think for the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights or a genuine 32b reasoning ('think') model that generates explicit chain-of-thought. Choose OLMo 3 32B Think if you need self-hosting or data privacy; GPT-6.1 Sol if you want a managed API.
GPT-6.1 Sol (OpenAI) and OLMo 3 32B Think (Allen Institute for AI) are two of the models people most often weigh against each other in 2026. GPT-6.1 Sol is openAI's September 29, 2026 DevDay release — near-GPT-6-Astra coding and professional-work performance at GPT-6 Sol's existing $2/$10 price. OLMo 3 32B Think is allen Institute for AI's fully-open 32B reasoning model - the rare release that ships the complete training data and process, not just the weights. 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: OLMo 3 32B Think ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-6.1 Sol is API-metered at $2/$10 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
- ▸Context window: GPT-6.1 Sol holds 16× more — 1.05M tokens (~1,575 pages) vs 65K (~98 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-6.1 Sol is the newer model by about 10 months (released September 29, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | GPT-6.1 Sol | OLMo 3 32B Think |
|---|---|---|
| Provider | OpenAI (US) | Allen Institute for AI (US) |
| Released | September 29, 2026 | November 20, 2025 |
| Context window | 1.05M tokens (~1,575 pages) | 65K (~98 pages) |
| Price (in/out) | $2/$10 per 1M tokens | Open weight (self-host / free) |
| Open weight? | No — API only | Yes — self-hostable |
| Modalities | text, image | text, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Nearly matches flagship GPT-6 Astra on agentic coding, computer use, and professional work, OpenAI says, at roughly one-fifth Astra's price
GPT-6.1 Sol
OpenAI's September 29, 2026 DevDay release — near-GPT-6-Astra coding and professional-work performance at GPT-6 Sol's existing $2/$10 price — and it carries the larger 1.05M tokens context.
Factual-accuracy error rate falls to 7.7% at low reasoning effort, down from GPT-6 Sol's 11.4%
GPT-6.1 Sol
OpenAI's September 29, 2026 DevDay release — near-GPT-6-Astra coding and professional-work performance at GPT-6 Sol's existing $2/$10 price — and it is the newer of the two.
Cached input priced at $0.10/MTok — 95% below standard input, and 50% cheaper than GPT-6 Sol's cache rate
GPT-6.1 Sol
GPT-6.1 Sol lists cached input priced at $0.10/MTok — 95% below standard input, and 50% cheaper than GPT-6 Sol's cache rate among its strengths; OLMo 3 32B Think does not.
The most fully transparent open release available - Ai2 publishes the complete weights, full Dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/RL code, not just final weights
OLMo 3 32B Think
Open weights make this possible at all — GPT-6.1 Sol is API-only, so it cannot leave the vendor's servers.
A genuine 32B reasoning ('Think') model that generates explicit chain-of-thought
OLMo 3 32B Think
Allen Institute for AI's fully-open 32B reasoning model - the rare release that ships the complete training data and process, not just the weights — and its weights are open while GPT-6.1 Sol is API-only.
Fully open under Apache 2.0 - free to self-host
OLMo 3 32B Think
OLMo 3 32B Think lists fully open under Apache 2.0 - free to self-host among its strengths; GPT-6.1 Sol does not.
Lowest cost at scale
OLMo 3 32B Think
Its weights are open, so at volume you pay for your own hardware instead of GPT-6.1 Sol's $2/$10 per 1M tokens.
Largest single-prompt input
GPT-6.1 Sol
Its 1.05M tokens window is about 16× larger than OLMo 3 32B Think's 65K, fitting roughly 1,575 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ OLMo 3 32B Think
At Open weight (self-host / free) it undercuts GPT-6.1 Sol, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-6.1 Sol
Larger 1.05M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ OLMo 3 32B Think
Open weights let you run it on your own hardware; GPT-6.1 Sol is API-only.
Anyone whose priority is nearly matches flagship gpt-6 astra on agentic coding, computer use, and professional work, openai says, at roughly one-fifth astra's price
→ GPT-6.1 Sol
It is specifically built for that.
Anyone whose priority is the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights
→ OLMo 3 32B Think
That is its strongest area.
GPT-6.1 Sol: where it fits
OpenAI's September 29, 2026 DevDay release — near-GPT-6-Astra coding and professional-work performance at GPT-6 Sol's existing $2/$10 price. Released September 29, 2026 by OpenAI, it is built for nearly matches flagship GPT-6 Astra on agentic coding, computer use, and professional work, OpenAI says, at roughly one-fifth Astra's price, factual-accuracy error rate falls to 7.7% at low reasoning effort, down from GPT-6 Sol's 11.4%, cached input priced at $0.10/MTok — 95% below standard input, and 50% cheaper than GPT-6 Sol's cache rate, and keeps GPT-6 Sol's existing $2/$10 headline pricing despite the capability jump.
Its trade-offs are real: launched in place of a hoped-for GPT-6.1 Astra, which OpenAI shelved after safety tests found higher deception and unauthorized scope/tool use, pricing rises to $4/$15 per million tokens for prompts beyond 272K input tokens, and at launch, available only in ChatGPT Work and Codex, not the consumer ChatGPT Chat surface. At $2 in / $10 out per million tokens, it sits in the mid price band.
OLMo 3 32B Think: where it fits
Allen Institute for AI's fully-open 32B reasoning model - the rare release that ships the complete training data and process, not just the weights. Released November 20, 2025 by Allen Institute for AI, it is built for the most fully transparent open release available - Ai2 publishes the complete weights, full Dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/RL code, not just final weights, a genuine 32B reasoning ('Think') model that generates explicit chain-of-thought, fully open under Apache 2.0 - free to self-host, and built specifically to let researchers reproduce and audit exactly how the model was trained.
Its trade-offs: a 65K context window is modest next to million-token frontier models, prioritizes full openness and reproducibility over topping raw capability leaderboards, and 32B scale trails much larger frontier and open MoE models on general benchmarks. 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. OLMo 3 32B Think gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-6.1 Sol 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-6.1 Sol and OLMo 3 32B Think 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.
See pricingFrequently asked questions
Is GPT-6.1 Sol or OLMo 3 32B Think 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-6.1 Sol leans toward nearly matches flagship gpt-6 astra on agentic coding, computer use, and professional work, openai says, at roughly one-fifth astra's price while OLMo 3 32B Think leans toward the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6.1 Sol or OLMo 3 32B Think?
OLMo 3 32B Think is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-6.1 Sol is API-metered at $2/$10 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-6.1 Sol — 1.05M tokens vs 65K, about 16× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-6.1 Sol and OLMo 3 32B Think together?
Yes — a multi-model platform like LumiChats gives you GPT-6.1 Sol, OLMo 3 32B Think 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-6.1 Sol or OLMo 3 32B Think?
GPT-6.1 Sol — released September 29, 2026, about 10 months after OLMo 3 32B Think.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.