Pick GPT-6 Sol for openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment or openai says it makes about half as many mistakes as gpt-5.6 sol. Pick Qwen 3.7 Max for long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7) or 1m-token long-document and full-codebase analysis. On a tight budget at scale, GPT-6 Sol is the value pick.
GPT-6 Sol (OpenAI, US) and Qwen 3.7 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 Sol is openAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. Qwen 3.7 Max is alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: nearly identical — $2/$10 per 1M tokens vs $2.5/$7.5 per 1M tokens. Cost will not be the deciding factor here.
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 Sol is the newer model by about 4 months (released September 22, 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.
Specifications
Spec
GPT-6 Sol
Qwen 3.7 Max
Provider
OpenAI (US)
Alibaba (China)
Released
September 22, 2026
May 20, 2026
Context window
1.05M tokens (~1,575 pages)
1M (~1,500 pages)
Price (in/out)
$2/$10 per 1M tokens
$2.5/$7.5 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
OpenAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment: GPT-6 Sol — OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens — and it runs cheaper at $2/$10 per 1M tokens.
OpenAI says it makes about half as many mistakes as GPT-5.6 Sol: GPT-6 Sol — OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens — and it is the newer of the two.
Priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30): GPT-6 Sol — At $2/$10 per 1M tokens it undercuts Qwen 3.7 Max ($2.5/$7.5 per 1M tokens), and that gap compounds at volume.
Long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7): Qwen 3.7 Max — Qwen 3.7 Max lists long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7) among its strengths; GPT-6 Sol does not.
1M-token long-document and full-codebase analysis: Qwen 3.7 Max — Qwen 3.7 Max lists 1M-token long-document and full-codebase analysis among its strengths; GPT-6 Sol does not.
MCP tool orchestration and multi-hour autonomous runs: Qwen 3.7 Max — Qwen 3.7 Max lists mCP tool orchestration and multi-hour autonomous runs among its strengths; GPT-6 Sol does not.
Lowest cost at scale: GPT-6 Sol — At $2/$10 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: GPT-6 Sol — At $2/$10 per 1M tokens it undercuts Qwen 3.7 Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-6 Sol — Larger 1.05M tokens window fits more in one prompt.
Anyone whose priority is openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment: GPT-6 Sol — It is specifically built for that.
Anyone whose priority is long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7): Qwen 3.7 Max — That is its strongest area.
An enterprise with regional data-residency rules: GPT-6 Sol or Qwen 3.7 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 Sol: where it fits
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. Released September 22, 2026 by OpenAI, it is built for openAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment, openAI says it makes about half as many mistakes as GPT-5.6 Sol, priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30), and 1.05M-token context window, input capped at 922K.
Its trade-offs are real: more reasoning capability than sibling GPT-6 Luna, but still positioned below flagship GPT-6 Astra, and cache-read pricing ($0.20/MTok) still costlier than Luna's ($0.01/MTok) for high-cache workloads. At $2 in / $10 out per million tokens, it sits in the mid price band.
Qwen 3.7 Max: where it fits
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. Released May 20, 2026 by Alibaba, it is built for long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7), 1M-token long-document and full-codebase analysis, mCP tool orchestration and multi-hour autonomous runs, and frontier intelligence at roughly half the price of US flagships.
Its trade-offs: text-only — no vision input (the Plus variant adds images), closed-weight, API-only — no self-hosting, trails GPT-5.5 and Claude Opus on the hardest one-shot reasoning, and chinese-jurisdiction data-residency considerations. At $2.5 in / $7.5 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 Sol (US) and Qwen 3.7 Max (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. GPT-6 Sol 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.
Frequently asked questions
Is GPT-6 Sol or Qwen 3.7 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 Sol leans toward openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment while Qwen 3.7 Max leans toward long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6 Sol or Qwen 3.7 Max?
GPT-6 Sol is cheaper — $2/$10 per 1M tokens vs $2.5/$7.5 per 1M tokens, roughly 1.3× 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 Sol and Qwen 3.7 Max together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Sol, Qwen 3.7 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 Sol or Qwen 3.7 Max?
GPT-6 Sol — released September 22, 2026, about 4 months after Qwen 3.7 Max.
GPT-6 Sol vs Qwen 3.7 Max
OpenAI · US | Alibaba · China · Updated June 2026
Quick verdict
Pick GPT-6 Sol for openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment or openai says it makes about half as many mistakes as gpt-5.6 sol. Pick Qwen 3.7 Max for long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7) or 1m-token long-document and full-codebase analysis. On a tight budget at scale, GPT-6 Sol is the value pick.
GPT-6 Sol (OpenAI, US) and Qwen 3.7 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 Sol is openAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. Qwen 3.7 Max is alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: nearly identical — $2/$10 per 1M tokens vs $2.5/$7.5 per 1M tokens. Cost will not be the deciding factor here.
▸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 Sol is the newer model by about 4 months (released September 22, 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 Sol
Qwen 3.7 Max
Provider
OpenAI (US)
Alibaba (China)
Released
September 22, 2026
May 20, 2026
Context window
1.05M tokens (~1,575 pages)
1M (~1,500 pages)
Price (in/out)
$2/$10 per 1M tokens
$2.5/$7.5 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
OpenAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment
GPT-6 Sol
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens — and it runs cheaper at $2/$10 per 1M tokens.
OpenAI says it makes about half as many mistakes as GPT-5.6 Sol
GPT-6 Sol
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens — and it is the newer of the two.
Priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30)
GPT-6 Sol
At $2/$10 per 1M tokens it undercuts Qwen 3.7 Max ($2.5/$7.5 per 1M tokens), and that gap compounds at volume.
Long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7)
Qwen 3.7 Max
Qwen 3.7 Max lists long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7) among its strengths; GPT-6 Sol does not.
1M-token long-document and full-codebase analysis
Qwen 3.7 Max
Qwen 3.7 Max lists 1M-token long-document and full-codebase analysis among its strengths; GPT-6 Sol does not.
MCP tool orchestration and multi-hour autonomous runs
Qwen 3.7 Max
Qwen 3.7 Max lists mCP tool orchestration and multi-hour autonomous runs among its strengths; GPT-6 Sol does not.
Lowest cost at scale
GPT-6 Sol
At $2/$10 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
→ GPT-6 Sol
At $2/$10 per 1M tokens it undercuts Qwen 3.7 Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-6 Sol
Larger 1.05M tokens window fits more in one prompt.
Anyone whose priority is openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment
→ GPT-6 Sol
It is specifically built for that.
Anyone whose priority is long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7)
→ Qwen 3.7 Max
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-6 Sol or Qwen 3.7 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 Sol: where it fits
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. Released September 22, 2026 by OpenAI, it is built for openAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment, openAI says it makes about half as many mistakes as GPT-5.6 Sol, priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30), and 1.05M-token context window, input capped at 922K.
Its trade-offs are real: more reasoning capability than sibling GPT-6 Luna, but still positioned below flagship GPT-6 Astra, and cache-read pricing ($0.20/MTok) still costlier than Luna's ($0.01/MTok) for high-cache workloads. At $2 in / $10 out per million tokens, it sits in the mid price band.
Qwen 3.7 Max: where it fits
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. Released May 20, 2026 by Alibaba, it is built for long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7), 1M-token long-document and full-codebase analysis, mCP tool orchestration and multi-hour autonomous runs, and frontier intelligence at roughly half the price of US flagships.
Its trade-offs: text-only — no vision input (the Plus variant adds images), closed-weight, API-only — no self-hosting, trails GPT-5.5 and Claude Opus on the hardest one-shot reasoning, and chinese-jurisdiction data-residency considerations. At $2.5 in / $7.5 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 Sol (US) and Qwen 3.7 Max (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. GPT-6 Sol 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 Sol and Qwen 3.7 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.
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 Sol leans toward openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment while Qwen 3.7 Max leans toward long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6 Sol or Qwen 3.7 Max?
GPT-6 Sol is cheaper — $2/$10 per 1M tokens vs $2.5/$7.5 per 1M tokens, roughly 1.3× 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 Sol and Qwen 3.7 Max together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Sol, Qwen 3.7 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 Sol or Qwen 3.7 Max?
GPT-6 Sol — released September 22, 2026, about 4 months after Qwen 3.7 Max.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.