GPT-6.1 Terra vs Qwen3 235B A22B (2507)
OpenAI · US | Alibaba · China · Updated June 2026
Quick verdict
Pick GPT-6.1 Terra for $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra or terminal-bench 4.0 of 50.3% at maximum reasoning effort, versus 21.5% for gpt-5.6 terra (openai-reported). Pick Qwen3 235B A22B (2507) for deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux) or exceptional multilingual and alignment results (79.2 arena-hard v2, 85.2 writingbench). Choose Qwen3 235B A22B (2507) if you need self-hosting or data privacy; GPT-6.1 Terra if you want a managed API.
GPT-6.1 Terra (OpenAI, US) and Qwen3 235B A22B (2507) (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 Terra is openAI's October 26, 2026 mid-tier model - a 1.05M-context, computer-use-capable GPT at $1/$5 per million tokens, half the price of its predecessor. Qwen3 235B A22B (2507) is an older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. 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: Qwen3 235B A22B (2507) ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-6.1 Terra 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: GPT-6.1 Terra holds 4× more — 1.05M tokens (~1,575 pages) vs 256K (~393 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 Terra is the newer model by about 15 months (released October 26, 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 Terra | Qwen3 235B A22B (2507) |
|---|---|---|
| Provider | OpenAI (US) | Alibaba (China) |
| Released | October 26, 2026 | July 21, 2025 |
| Context window | 1.05M tokens (~1,575 pages) | 256K (~393 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, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
$1/$5 per million tokens (cached input $0.05) - half the price of GPT-6.1 Sol and GPT-5.6 Terra
GPT-6.1 Terra
Its 1.05M tokens window holds about 4× more than Qwen3 235B A22B (2507)'s 256K in a single prompt.
Terminal-Bench 4.0 of 50.3% at maximum reasoning effort, versus 21.5% for GPT-5.6 Terra (OpenAI-reported)
GPT-6.1 Terra
Qwen3 235B A22B (2507) is comparatively weak here — text-only with no vision, and the absence of a thinking mode caps its hardest reasoning
1.05M-token context with up to 128K output tokens, plus image input and computer use via the Responses API
GPT-6.1 Terra
OpenAI's October 26, 2026 mid-tier model - a 1.05M-context, computer-use-capable GPT at $1/$5 per million tokens, half the price of its predecessor — and it carries the larger 1.05M tokens context.
Deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux)
Qwen3 235B A22B (2507)
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding — and its weights are open while GPT-6.1 Terra is API-only.
Exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench)
Qwen3 235B A22B (2507)
Qwen3 235B A22B (2507) lists exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench) among its strengths; GPT-6.1 Terra does not.
Outstanding structured logic — 95.0 on ZebraLogic
Qwen3 235B A22B (2507)
Qwen3 235B A22B (2507) lists outstanding structured logic — 95.0 on ZebraLogic among its strengths; GPT-6.1 Terra does not.
Lowest cost at scale
Qwen3 235B A22B (2507)
Its weights are open, so at volume you pay for your own hardware instead of GPT-6.1 Terra's $1/$5 per 1M tokens.
Largest single-prompt input
GPT-6.1 Terra
Its 1.05M tokens window is about 4× larger than Qwen3 235B A22B (2507)'s 256K, fitting roughly 1,575 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen3 235B A22B (2507)
At Open weight (self-host / free) it undercuts GPT-6.1 Terra, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-6.1 Terra
Larger 1.05M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Qwen3 235B A22B (2507)
Open weights let you run it on your own hardware; GPT-6.1 Terra is API-only.
Anyone whose priority is $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra
→ GPT-6.1 Terra
It is specifically built for that.
Anyone whose priority is deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux)
→ Qwen3 235B A22B (2507)
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-6.1 Terra or Qwen3 235B A22B (2507)
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 Terra: where it fits
OpenAI's October 26, 2026 mid-tier model - a 1.05M-context, computer-use-capable GPT at $1/$5 per million tokens, half the price of its predecessor. Released October 26, 2026 by OpenAI, it is built for $1/$5 per million tokens (cached input $0.05) - half the price of GPT-6.1 Sol and GPT-5.6 Terra, terminal-Bench 4.0 of 50.3% at maximum reasoning effort, versus 21.5% for GPT-5.6 Terra (OpenAI-reported), 1.05M-token context with up to 128K output tokens, plus image input and computer use via the Responses API, and error rate on OpenAI's hard-prompt set falls from 53.6% (GPT-5.6 Terra) to 16.7% at low effort and 4.3% at max effort.
Its trade-offs are real: openAI still positions Sol and Astra as the higher-capability choices for demanding coding problems, requests above 272K input tokens are billed at 2x input and 1.5x output for the whole request, closed weights and no fine-tuning support, and benchmark figures are vendor-reported; no SWE-bench Verified or MRCR numbers published. At $1 in / $5 out per million tokens, it sits in the budget price band.
Qwen3 235B A22B (2507): where it fits
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. Released July 21, 2025 by Alibaba, it is built for deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux), exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench), outstanding structured logic — 95.0 on ZebraLogic, and no thinking mode, which makes latency and token spend entirely predictable.
Its trade-offs: nearly a year old and superseded — Artificial Analysis now steers users to Qwen3.5-397B instead, text-only with no vision, and the absence of a thinking mode caps its hardest reasoning, coding is weak by 2026 standards, and it publishes no SWE-Bench score to compare on, and its 235B weights need roughly 438GB in BF16, far beyond consumer hardware. 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. Qwen3 235B A22B (2507) gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-6.1 Terra 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 Terra and Qwen3 235B A22B (2507) 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 Terra or Qwen3 235B A22B (2507) 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 Terra leans toward $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra while Qwen3 235B A22B (2507) leans toward deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6.1 Terra or Qwen3 235B A22B (2507)?
Qwen3 235B A22B (2507) is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-6.1 Terra 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?
GPT-6.1 Terra — 1.05M tokens vs 256K, about 4× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-6.1 Terra and Qwen3 235B A22B (2507) together?
Yes — a multi-model platform like LumiChats gives you GPT-6.1 Terra, Qwen3 235B A22B (2507) 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 Terra or Qwen3 235B A22B (2507)?
GPT-6.1 Terra — released October 26, 2026, about 15 months after Qwen3 235B A22B (2507).
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.