GPT-6.1 Sol vs Qwen 3.6 Plus
OpenAI · US | Alibaba · China · 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 Qwen 3.6 Plus for strong gpqa diamond science reasoning or open-weight and budget-friendly. On a tight budget at scale, Qwen 3.6 Plus is the value pick.
GPT-6.1 Sol (OpenAI, US) and Qwen 3.6 Plus (Alibaba, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. Qwen 3.6 Plus is alibaba's open-weight contender — surprising benchmark wins at a budget price. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: Qwen 3.6 Plus is about 6.2× cheaper on input ($0.325/$1.95 per 1M tokens vs $2/$10 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: 1.05M tokens vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
- ▸Recency: GPT-6.1 Sol is the newer model by about 6 months (released September 29, 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 | GPT-6.1 Sol | Qwen 3.6 Plus |
|---|---|---|
| Provider | OpenAI (US) | Alibaba (China) |
| Released | September 29, 2026 | April 2, 2026 |
| Context window | 1.05M tokens (~1,575 pages) | 1M (~1,500 pages) |
| Price (in/out) | $2/$10 per 1M tokens | $0.325/$1.95 per 1M tokens |
| Open weight? | No — API only | No — API only |
| Modalities | text, image | text, image, code |
| SWE-Bench Verified | Not published | 78.8% |
| 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 is the newer of the two.
Factual-accuracy error rate falls to 7.7% at low reasoning effort, down from GPT-6 Sol's 11.4%
GPT-6.1 Sol
GPT-6.1 Sol lists factual-accuracy error rate falls to 7.7% at low reasoning effort, down from GPT-6 Sol's 11.4% among its strengths; Qwen 3.6 Plus does not.
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; Qwen 3.6 Plus does not.
Strong GPQA Diamond science reasoning
Qwen 3.6 Plus
Alibaba's open-weight contender — surprising benchmark wins at a budget price — and it runs cheaper at $0.325/$1.95 per 1M tokens.
Open-weight and budget-friendly
Qwen 3.6 Plus
At $0.325/$1.95 per 1M tokens it undercuts GPT-6.1 Sol ($2/$10 per 1M tokens), and that gap compounds at volume.
1M context
Qwen 3.6 Plus
Qwen 3.6 Plus lists 1M context among its strengths; GPT-6.1 Sol does not.
Lowest cost at scale
Qwen 3.6 Plus
At $0.325/$1.95 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen 3.6 Plus
At $0.325/$1.95 per 1M tokens 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.
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 strong gpqa diamond science reasoning
→ Qwen 3.6 Plus
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-6.1 Sol or Qwen 3.6 Plus
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
Qwen 3.6 Plus: where it fits
Alibaba's open-weight contender — surprising benchmark wins at a budget price. Released April 2, 2026 by Alibaba, it is built for strong GPQA Diamond science reasoning, open-weight and budget-friendly, 1M context, and multilingual coverage.
Its trade-offs: less Western ecosystem tooling, and benchmark coverage still maturing. At $0.325 in / $1.95 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." GPT-6.1 Sol (US) and Qwen 3.6 Plus (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Qwen 3.6 Plus 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 GPT-6.1 Sol and Qwen 3.6 Plus 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 Qwen 3.6 Plus better for coding?
Public SWE-Bench figures are not available for GPT-6.1 Sol, 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 Qwen 3.6 Plus leans toward strong gpqa diamond science reasoning, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6.1 Sol or Qwen 3.6 Plus?
Qwen 3.6 Plus is cheaper — $2/$10 per 1M tokens vs $0.325/$1.95 per 1M tokens, roughly 6.2× apart on input.
Which has the bigger context window?
Effectively neither — 1.05M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GPT-6.1 Sol and Qwen 3.6 Plus together?
Yes — a multi-model platform like LumiChats gives you GPT-6.1 Sol, Qwen 3.6 Plus 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 Qwen 3.6 Plus?
GPT-6.1 Sol — released September 29, 2026, about 6 months after Qwen 3.6 Plus.
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.