Qwen vs ChatGPT — which actually wins in 2026?
Qwen and ChatGPT split the board. Qwen Studio is free with no consumer paid tier, and Qwen3.7 Max is cheaper on output tokens. ChatGPT leads on composite intelligence (Artificial Analysis Index 55 vs 46), terminal agents, and ecosystem — GPT Store, Codex, per-seat Business. Raw reasoning is a tie (GPQA Diamond 92.4 vs 92.9). Choose Qwen for free chat, cheap output and China-region reach; choose ChatGPT for coding agents, ecosystem depth and teams.
| Category | Winner | Margin |
|---|---|---|
| General reasoning · GPQA Diamond | ·Tie | 92.4 vs 92.9 — half a point apart on a saturated board (llm-stats, Jul 2026) |
| Composite intelligence · AA Intelligence Index v4.1 | BChatGPT | GPT-5.6 Terra 55 vs Qwen3.7 Max 46 — a real gap across 9 evaluations |
| Terminal / agentic coding · Terminal-Bench v2.1 | BChatGPT | GPT-5.6 Terra scores 88.0; Qwen3.7 Max has no neutral terminal-agent score at all |
| Knowledge breadth · MMLU-Pro | ·Not comparable | Qwen3.7 Max 89.6 tops the llm-stats board; no GPT-5.6 entry — no head-to-head |
| Patch-writing · SWE-bench Verified | AQwen | Qwen3.7 Max 80.4 on llm-stats; OpenAI does not submit GPT-5.6 to this board |
| API output cost · per 1M tokens | AQwen | Qwen3.7 Max is roughly half the output rate of GPT-5.6 Terra — see the table |
| API input cost · per 1M tokens | BChatGPT | GPT-5.6 Terra edges it on input, and adds a 10× cheaper cached-input rate |
| Context window · API model | ·Tie | Qwen3.7 Max 1M vs GPT-5.6 Terra 1.05M — a rounding-level difference |
| Open weights · self-host path | AQwen | Neither flagship is open, but Qwen3.6-27B and 35B-A3B ship under Apache 2.0 |
| Free tier · what $0 buys | AQwen | Qwen Studio is free with no paid tier above it; ChatGPT Free is capped by design |
| Ecosystem · store, agents, connectors | BChatGPT | GPT Store, custom GPTs, Codex, scheduled tasks, Microsoft 365 / Slack / GitHub connectors |
| Team / enterprise · seats + admin | BChatGPT | ChatGPT Business is a real per-seat tier with SAML SSO; Qwen has no per-seat app plan |
| Data residency · where prompts live | ·Tie | Model Studio offers 6 regions incl. Frankfurt; ChatGPT Enterprise offers 10 incl. EU |
| Best overall | ·Depends | See the decision tree below |
If you want free chat and cheap output tokens.
- Free app — Qwen Studio is free to use with no consumer subscription sitting above it
- Cheaper output — Qwen3.7 Max's output rate is roughly half GPT-5.6 Terra's, where agentic bills concentrate
- Open-weight line — Qwen3.6-27B and 35B-A3B ship under Apache 2.0 if you need to self-host
- Region choice — Model Studio runs in Singapore, US, Frankfurt, Tokyo, Hong Kong and Beijing, and Beijing cuts token cost sharply
- Full app surface — web, iOS, Android, macOS and Windows, with search, memory, artifacts and image/video generation
If you need agents, ecosystem and teams.
- Composite lead — 55 vs 46 on the Artificial Analysis Intelligence Index across nine evaluations
- Terminal agents — 88.0 on Terminal-Bench v2.1, a board Qwen3.7 Max does not appear on
- Ecosystem — GPT Store, custom GPTs, Codex, scheduled tasks and first-party connectors
- Teams — a per-seat Business tier with SAML SSO, MFA and no training on business data by default
- Cached input — a 10× discount on repeated context that Qwen does not itemise
| Aspect | Qwen | ChatGPT |
|---|---|---|
| Free tierWhat a non-paying user gets | $0 · full app Qwen Studio on web, iOS, Android, macOS and Windows; search, memory, file analysis to 1M tokens, image and video generation; no message caps published, no ads A wins | $0 · GPT-5.5 Instant Limited messages, uploads, deep research and memory; 27K Instant context window; no Projects or custom GPTs |
| Entry subscriptionCheapest paid path to more usage | None — app is free Alibaba sells no consumer Plus/Pro plan for Qwen Studio; heavier use goes through the pay-per-token Model Studio API A wins | $20/mo · ChatGPT Plus GPT-5.6 Sol reasoning, Projects, scheduled tasks, custom GPTs, expanded deep research; ChatGPT Go sits below at ~$8/mo and may show ads |
| Developer planFixed monthly coding subscription | ¥200/mo · Coding Plan Pro 90K requests/mo (45K weekly, 6K per 5 hours) on Qwen3.7-Plus and the coder models; works with Qwen Code, Claude Code and Cline; the Lite tier was withdrawn in Apr 2026 and Qwen3.7 Max is not included | $200/mo · ChatGPT Pro 5× or 20× Plus usage, GPT-5.6 Sol Pro, unlimited GPT-5.6 Terra, maximum Codex tasks, 400K reasoning context; a ~$100/mo Pro tier sits below it B wins |
| API · inputper 1M tokens · from snapshot | $2.77 | $2.50 B wins |
| API · outputper 1M tokens · from snapshot | $8.31 A wins | $15.0 |
| Effective API costBlended workload $/1M · from snapshot | $3.21 | $1.80 B wins |
| API context windowMax input tokens · from snapshot | 1M | 1.05M B wins |
| Real cost / 1M charsTokenizer-adjusted prose — the tokenizer tax | $0.53 | $0.47 B wins |
| Team / enterpriseSeats, SSO, admin | API / self-host No per-seat app tier; teams run Model Studio keys per region, or host the Apache-2.0 Qwen3.6 weights themselves | $20–25/seat · Business About $20/seat billed annually, $25 monthly, minimum 2 users; SAML SSO, MFA, no training on business data; Enterprise adds SCIM and data residency and is quoted by sales B wins |
| Capability | Qwen | ChatGPT |
|---|---|---|
| API context window | 1M tokens | 1.05M tokens |
| Flagship weights | ✗ Qwen3.7 Max is API-only | ✗ Closed |
| Open-weight siblings | ✓ Qwen3.6-27B / 35B-A3B, Apache 2.0 | ~ Separate open line only |
| Consumer subscription | ✗ None — app is free | Go / Plus / Pro |
| Default chat model | Qwen3.7-Plus | GPT-5.5 Instant |
| Flagship in the chat app | ~ Max is API-tier, not the app default | ~ Terra is Pro / Codex, not the default |
| Vision / image input | ✓ Images, audio and video understanding | ✓ Images and files |
| Image generation | ✓ In-app | ✓ In-app |
| Video generation | ✓ Text-to-video in Qwen Studio | ~ Not on the plan comparison |
| Voice mode | ✓ Voice conversations | ✓ Voice, plus voice with video |
| Web search | ✓ Built-in | ✓ Built-in |
| Persistent memory | ✓ Qwen Chat Memory | ✓ Memory with past chats |
| File uploads / data analysis | ✓ CSV, Excel, docs to 1M tokens | ✓ Limited on Free, expanded on paid |
| Code artifacts / sandbox | ✓ Artifacts (HTML + SVG) | ✓ Canvas + Codex |
| Coding agent integration | ✓ Qwen Code, Claude Code, Cline | ✓ Codex across desktop and mobile |
| Custom assistants / store | ✗ | ✓ Custom GPTs + GPT Store |
| MCP support | ~ Responses API; Plus/Flash series, not Max | ✓ Connectors + apps |
| Scheduled tasks | ✗ Not published | ✓ Plus and above |
| Desktop apps | ✓ macOS + Windows | ✓ macOS + Windows |
| Mobile apps | iOS + Android | iOS + Android |
| SAML SSO | ✗ No per-seat app tier | ✓ Business + Enterprise |
| SCIM provisioning | ✗ Not for the app | ✓ Enterprise |
| API regions | Singapore, US, Frankfurt, Tokyo, HK, Beijing | ~ Residency on Enterprise only |
| Training on your data | ✗ Model Studio states no training | ~ Opt-out on consumer; off by default on Business |
| Batch discount | ✓ 50% off | ✓ 50% off |
| Cached-input rate | ~ Discounted, not itemised | ✓ 10× off standard input |
The numbers, not the spin.
Qwen
The free assistant with a paid-grade model behind it — strong on knowledge and patch-writing, cheap on output tokens, and the only side with a genuine Apache-2.0 fallback.
Strengths
- Free app — Qwen Studio is free to use with no consumer tier above it, on web, iOS, Android, macOS and Windows
- Cheap output — Qwen3.7 Max's output rate is around half GPT-5.6 Terra's, which is where agentic and generation bills land
- Knowledge breadth — 89.6 on MMLU-Pro tops the llm-stats board, ahead of every model with a published entry
- Patch-writing — 80.4 on SWE-bench Verified puts it in the top tier of models that submit to that board
- Open-weight fallback — Qwen3.6-27B and 35B-A3B are Apache 2.0, so a self-host path exists one version back
- Region control — Model Studio runs in Singapore, US, Frankfurt, Tokyo, Hong Kong and Beijing, with per-region keys and residency
Weaknesses
- Qwen3.7 Max is closed — no Hugging Face checkpoint, no GGUF, API-only despite the family's open reputation
- No neutral terminal-agent score at all — it isn't on the Terminal-Bench v2.1 board, so agentic claims can't be checked
- Composite intelligence trails: 46 vs 55 on the Artificial Analysis Index
- No per-seat team tier, no SSO, no SCIM for the app
- MCP is limited to the Plus and Flash series via the Responses API — Qwen3.7 Max is not on the supported list
- Cached-input pricing is discounted but not itemised, so repeated-context costs are hard to model
Best for
- Anyone who wants a capable assistant at $0 with no upsell
- Output-heavy API workloads where the token bill concentrates on generation
- Teams that need a Frankfurt, Tokyo or Singapore endpoint
- Builders who want an Apache-2.0 escape hatch from vendor lock-in
- Knowledge-heavy and patch-writing tasks
ChatGPT
The default Western assistant — the widest ecosystem, the strongest neutral agentic score, and the only side of this pair with a real per-seat team product.
Strengths
- Composite lead — 55 vs 46 on the Artificial Analysis Intelligence Index, measured across nine evaluations
- Terminal agents — 88.0 on Terminal-Bench v2.1, near the top of a board Qwen doesn't appear on
- Ecosystem — GPT Store, custom GPTs, Codex, scheduled tasks, Projects and connectors to Microsoft 365, Slack, GitHub and Figma
- Teams — a per-seat Business tier with SAML SSO, MFA, admin console and no training on business data by default
- Cached input — repeated context costs a tenth of the standard input rate, which reshapes long-prompt economics
- Residency — Enterprise offers data residency across ten regions including the EU and UK
Weaknesses
- Pricier output — roughly double Qwen3.7 Max per 1M output tokens
- Everyday chat defaults to GPT-5.5 Instant; GPT-5.6 Terra is limited even on Plus and only unlimited on Pro
- Free tier is capped on messages, uploads, deep research and memory, with a 27K Instant context window
- No open weights for the frontier line — no self-host path at this tier
- Absent from the llm-stats MMLU-Pro and SWE-bench Verified boards, so parts of the comparison have no head-to-head
Best for
- Coding agents and terminal-loop work
- Teams needing SSO, admin controls and shared workspaces
- Ecosystem-heavy workflows built on custom GPTs and connectors
- Long-prompt applications that benefit from cached input
- Buyers who want the widest third-party integration surface
Someone who refuses to pay for an assistant
You want a competent everyday assistant — search, file analysis, images, voice — and you have no intention of paying $20 a month for it.
Reasoning: Qwen Studio is free with no tier above it, and it ships search, memory, artifacts, file analysis to 1M tokens, and image and video generation on web, mobile and desktop. ChatGPT Free is capped by design on messages, uploads, deep research and memory, with a 27K Instant context window, and the cheaper Go tier may carry ads. At $0 the gap is not close.
Engineer running autonomous coding loops
Your agent writes patches, runs tests and iterates in a terminal, and every failed step costs you attention and tokens.
Reasoning: GPT-5.6 Terra scores 88.0 on Terminal-Bench v2.1 and 55 on the composite Intelligence Index. Qwen3.7 Max isn't on the Terminal-Bench board at all — its 80.4 on SWE-bench Verified shows it writes strong patches, but that measures a different thing from driving a terminal unattended. Without a neutral agentic score, the defensible pick is ChatGPT.
API builder whose bill is all output tokens
You generate long responses at volume — summaries, drafts, structured extractions — and output dominates your invoice.
Reasoning: Qwen3.7 Max's output rate is roughly half GPT-5.6 Terra's, and input is close enough that the blend tilts Qwen's way on generation-heavy traffic. The counterweight is caching: if your prompts repeat, Terra's cached input at a tenth of standard input can claw a lot of that back. Check the blended row and the tokenizer-tax row against your own input/output ratio before you commit.
Team of twelve standardising on one assistant
You need shared seats, an admin console, SSO, and a written promise that your work isn't training anyone's model.
Reasoning: ChatGPT Business is a real per-seat product — roughly $20/seat annually or $25 monthly from two users, with SAML SSO, MFA and no training on business data by default. Qwen has no per-seat app plan; a team would share Model Studio API keys or self-host the open Qwen3.6 weights. For seats and admin today, this isn't a contest.
EU company that needs prompts to stay in Europe
Legal will not sign off unless you can name the region your prompts are processed in and keep it inside the EU.
Reasoning: Both sides can do it, by different routes. Model Studio runs a Frankfurt region with per-region keys that don't interchange, available on ordinary pay-as-you-go. ChatGPT offers EU data residency, but on Enterprise — a sales-quoted contract. If you want an EU endpoint without a procurement cycle, Qwen gets you there faster; if you already have an Enterprise agreement, ChatGPT is the simpler path.
Researcher who wants an escape hatch from lock-in
You'll build on a hosted API now but you want a credible path to running the model yourself if terms, prices or availability change.
Reasoning: Neither flagship is downloadable — Qwen3.7 Max is API-only with no Hugging Face checkpoint, which surprises people who know Qwen as the open-weights vendor. But Qwen3.6-27B and 35B-A3B are Apache 2.0 and one version behind, so a self-host fallback exists at a known quality level. OpenAI's frontier line offers nothing equivalent.
Straight from the threads.
for tasks like organizing messy data dumps or reasoning through complex logic puzzles, Qwen3.5 is matching it step-for-step. The native multimodal agent feature even feels a bit more "proactive" than ChatGPT's vision.
I use qwen3.6 in Hermes and qwen or Hermes keeps messing up simple coding tasks that I have ChatGPT fix.
The only reason I still use ChatGPT is for its top-tier voice transcription in its mobile app. On PC, I use only Qwen, whether via their chat interface or locally.
Qwen in the web app now has memory and remembers previous chats, the Qwen3.5 models are insanely good all rounders, and their 27B model is just crazy good for its size.
Frequently asked.
Common questions about this comparison, with sources where they matter.
Q · 01 Is Qwen or ChatGPT better overall? +
92.4 vs 92.9. ChatGPT leads on composite intelligence (Artificial Analysis Index 55 vs 46), terminal agents, ecosystem and team features. Qwen leads on price at the consumer end (its app is free), on output-token cost, on MMLU-Pro and SWE-bench Verified where OpenAI doesn't submit, and it has an Apache-2.0 self-host fallback. Pick by workload — see the decision tree above.Q · 02 Is Qwen free? +
chat.qwen.ai is free to use with no consumer subscription above it — search, memory, artifacts, file analysis to 1M tokens and image/video generation are included, across web, iOS, Android, macOS and Windows. The API is separate and pay-per-token through Alibaba Cloud Model Studio, and there's a fixed-price Qwen Coding Plan Pro at ¥200/mo for coding-agent use.Q · 03 Is Qwen open source? +
Qwen3.6-27B and Qwen3.6-35B-A3B are published under Apache 2.0. So a self-host path exists, but one generation behind the model in this comparison. Alibaba hasn't committed to opening 3.7.Q · 04 Which is cheaper? +
Q · 05 Which is better for coding? +
80.4 on SWE-bench Verified — strong patch-writing. But GPT-5.6 Terra scores 88.0 on Terminal-Bench v2.1, and Qwen3.7 Max isn't on that board, so there's no neutral evidence for its agentic-terminal ability. For autonomous loops, ChatGPT is the safer call. If coding is your main workload, also weigh Claude vs ChatGPT.Q · 06 Does ChatGPT run GPT-5.6 Terra by default? +
Q · 07 Where does my data go with Qwen? +
Q · 08 Can I use both? +
Q · 09 Which is better in non-English languages? +
89.6 and leads llm-stats outright — though GPT-5.6 has no entry there, so that's not a head-to-head. Both handle major European languages well. Test with your own material and register rather than trusting either leaderboard for your specific language.