GPT-6.1 Sol vs Qwen 3.8-Max

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 3.8-Max for near-frontier quality at value pricing — artificial analysis intelligence index 58 or large 1m-token context with multimodal input (text, image, video).

GPT-6.1 Sol (OpenAI, US) and Qwen 3.8-Max (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 3.8-Max is alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.

Key differences at a glance

Side-by-side specs

SpecGPT-6.1 SolQwen 3.8-Max
ProviderOpenAI (US) Alibaba (China)
ReleasedSeptember 29, 2026 August 3, 2026
Context window1.05M tokens (~1,575 pages) 1M (~1,573 pages)
Price (in/out)$2/$10 per 1M tokens $2/$6 per 1M tokens
Open weight?No — API only No — API only
Modalitiestext, image text, image, video, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot 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

Qwen 3.8-Max is comparatively weak here — flashier coding/agentic benchmarks (e.g. Terminal-Bench 86.6) are Alibaba's own, not independently reproduced

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; Qwen 3.8-Max does not.

Near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58

Qwen 3.8-Max

GPT-6.1 Sol is comparatively weak here — pricing rises to $4/$15 per million tokens for prompts beyond 272K input tokens

Large 1M-token context with multimodal input (text, image, video)

Qwen 3.8-Max

Qwen 3.8-Max lists large 1M-token context with multimodal input (text, image, video) among its strengths; GPT-6.1 Sol does not.

Mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token

Qwen 3.8-Max

Qwen 3.8-Max lists mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token among its strengths; GPT-6.1 Sol does not.

Which should you pick?

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 near-frontier quality at value pricing — artificial analysis intelligence index 58

→ Qwen 3.8-Max

That is its strongest area.

An enterprise with regional data-residency rules

→ GPT-6.1 Sol or Qwen 3.8-Max

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 3.8-Max: where it fits

Alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped. Released August 3, 2026 by Alibaba, it is built for near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58, large 1M-token context with multimodal input (text, image, video), mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token, and $2/$6 per million tokens — far below US flagships like Claude Opus 5 and GPT-5.6 Sol.

Its trade-offs: open weights were announced for release but had not shipped as of mid-August 2026 — a closed API for now, active-parameter count is not officially disclosed by Alibaba, flashier coding/agentic benchmarks (e.g. Terminal-Bench 86.6) are Alibaba's own, not independently reproduced, and trails the very top models (Opus 5, Fable 5, GPT-5.6 Sol) on independent tests. At $2 in / $6 out per million tokens, it sits in the mid 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 3.8-Max (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. 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 3.8-Max 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 pricing

Frequently asked questions

Is GPT-6.1 Sol or Qwen 3.8-Max 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 Qwen 3.8-Max leans toward near-frontier quality at value pricing — artificial analysis intelligence index 58, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, GPT-6.1 Sol or Qwen 3.8-Max?

They are priced almost identically, so cost will not decide between them.

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 3.8-Max together?

Yes — a multi-model platform like LumiChats gives you GPT-6.1 Sol, Qwen 3.8-Max 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 3.8-Max?

GPT-6.1 Sol — released September 29, 2026, about 57 days after Qwen 3.8-Max.

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.