Key Terms
- Bailian (Model Studio) - Alibaba Cloud's managed LLM platform providing API access, token billing, and subscriptions for Qwen plus third-party models (DeepSeek, Kimi, GLM, MiniMax, Xiaomi MiMo, StepFun). Source: Alibaba – Models
- Token Plan - Credits-based subscription for use inside coding tools (Claude Code, Cursor, Qwen Code, Codex, Qoder, OpenClaw). Personal edition: Lite ¥39, Essential ¥79, Standard ¥139, Pro ¥499/month (promotional). Team edition: ¥150/550/1,398 per seat/month. Beijing region only. Source: Alibaba – Token Plan Overview
- Credits - Token Plan billing unit. Personal Lite includes 11,500 Credits/month; Pro includes 180,000. Overage requires a ¥100 usage pack (20,000 Credits, max 5). Per-model Credit rates are not published. Source: Alibaba – Token Plan Overview
- Coding Plan - legacy flat-rate subscription (¥200/month Pro, per-request billing: 6,000 requests/5 hours, 45,000/week, 90,000/month). Lite closed to new purchase March 20, 2026; Pro is limited-quantity with daily 09:30 (UTC+8) restocks. Source: Alibaba – Coding Plan
- Prime mode (优速模式) - a high-throughput serving option delivering 1.5 to 2x standard TPS, billed per token. New September listing: qwen3.8-max-prime at ¥24/¥72 per MTok with no free quota. Source: Alibaba – Prime Mode
- Tiered pricing - input price rises with single-request input size. Example: qwen3.7-plus is ¥2/MTok input up to 256K, ¥6/MTok from 256K to 1M. Source: Alibaba – Billing For Model Studio
- Context caching - cached input tokens bill at discounted rates (explicit cache creation 125% of input price, cache hit 10%); input prices in the tables exclude cache pricing. Source: Alibaba – Billing For Model Studio
- Batch API - asynchronous inference at 50% of real-time input/output price on supported models (qwen3.8-max, qwen3.7-plus, others); cannot combine with caching. Source: Alibaba – Billing For Model Studio
Latest Changes
Changes since the 2026-08 report.
- New snapshot: qwen3.8-max-0902 (added 2026-09-02). Deeper coding ("engineering-grade projects and long-horizon autonomous development"), stronger collaborative-agent multi-tool orchestration, and improved vision/chart reasoning, at unchanged ¥12/¥36 per MTok with 1M context and thinking mode. Source: Alibaba – Newly Released Models
- New listing: qwen3.8-max-prime at ¥24/¥72 per MTok. Prime mode provides 1.5 to 2x standard TPS for latency-sensitive coding agents; exactly double the standard flagship price, no free quota, and it does not appear in the Prime-mode doc's supported-models table (which still lists only GLM models). Source: Alibaba – Billing For Model Studio , Alibaba – Prime Mode
- New models: qwen3.8-omni-flash (2026-09-17) and qwen3.8-omni-flash-realtime (2026-09-21). Omni-flash accepts text/image/audio/video input with text output, thinking and non-thinking modes, function calling, web search, and context caching; the realtime variant adds multi-channel audio/video aggregation and remote MCP tool calling over WebSocket/WebRTC/AOQ. Sources: Alibaba – Newly Released Models
- Visible public discount returns: qwen3.7-plus limited-time 20% off. The billing page now shows the qwen3.7-plus alias at 限时8折 (effective ¥1.6/¥6.4 per MTok at ≤256K, ¥4.8/¥19.2 at 256K-1M), a partial reversal of August's pattern where active discounts were visible only in the console. No end date published. Source: Alibaba – Billing For Model Studio
- Retrieval refresh (2026-09-01): qwen3.7-text-rerank and qwen3.7-text-embedding-flash. The reranker improves code retrieval, instruction-following, and agentic/memory retrieval versus qwen3-rerank (websearch +~35%); embedding-flash covers 201 languages, 128K documents, and sparse embeddings. Source: Alibaba – Newly Released Models
- Marketplace additions: deepseek-v4.1-flash (2026-09-13 direct, 2026-09-21 vanchin), ZHIPU/GLM-5.3-FlashX (2026-09-21, 200 tokens/s), and stepfun/step-5-preview (2026-09-21, 600B total/27B active, 1M context, agentic-coding flagship). Xiaomi's mimo-v2.5-pro (added 2026-05-18, strong SWE-bench Pro/ClawEval results per its release note) is now featured on the catalog's headline text-generation row. Source: Alibaba – Newly Released Models , Alibaba – Models
- Pricing flat across the Qwen3.8 lineup. qwen3.8-max ¥12/¥36, qwen3.8-2.4t-a95b ¥12/¥36, qwen3.8-27b ¥3/¥12, qwen3.8-flash ¥0.8/¥2.7 (flat to 1M), all unchanged versus August; Singapore international rates for 3.8-max are ¥14.988/¥44.965, below qwen3.7-max's ¥18.736/¥56.207. Source: Alibaba – Billing For Model Studio
- Coding Plan Pro model list still has no Qwen3.8 models. Recommended models remain qwen3.7-plus, qwen3.6-plus, kimi-k2.5, glm-5, MiniMax-M2.5; Pro is ¥200/month (first month ¥39.90) with daily 09:30 restocked inventory. Source: Alibaba – Coding Plan
- Geopolitical escalation. Anthropic's September 10 threat-intelligence report details industrial-scale distillation campaigns from Alibaba; on September 13, US agencies accused top Chinese AI companies including Alibaba of systematically copying American models. Sources: TechCrunch – Anthropic Details Distillation Campaigns From Alibaba Moonshot Ai And Deepseek , Nbcnews – Us Accuses China Ai Developers Deepseek Alibaba Copying American Ai Rcna596696
- Announcement (community-reported): At the Apsara Conference (~Sep 22), Alibaba announced Qwen 4 per a 2.1K-upvote r/LocalLLaMA thread; no Qwen 4 models, pricing, or docs were public as of the Sep 30 cutoff, and Aliyun's model list still tops out at qwen3.8. Track for October. Reddit – Qwen 4 Announced At Apsara Conference
Plans
Annual billing is not offered on any plan; all prices below are monthly. Promotional prices are marked; no promo end dates are published.
| Plan | Price (monthly) | Price (annual) | Usage limits | Key inclusions |
|---|---|---|---|---|
| Pay-as-you-go | Per-token (see API Pricing) | n/a | Undisclosed RPM/TPM | All Qwen + third-party models; free tier 1M tokens per model (90-day validity, Beijing region only) |
| Token Plan Personal Lite | ¥39 (orig ¥60) | not offered | 11,500 Credits/month | Claude Code, Cursor, Qwen Code, Codex, Qoder, OpenClaw; 1-2 concurrent agents |
| Token Plan Personal Essential | ¥79 (orig ¥120) | not offered | 25,500 Credits/month | Same tools; 2-3 concurrent agents |
| Token Plan Personal Standard | ¥139 (orig ¥180) | not offered | 45,000 Credits/month | Same tools; 3-4 concurrent agents; AgentStudio free quota and discounts |
| Token Plan Personal Pro | ¥499 (orig ¥600) | not offered | 180,000 Credits/month | Same tools; 6-8 concurrent agents; AgentStudio benefits |
| Personal usage pack | ¥100/pack | n/a | 20,000 Credits, 1-month validity | Max 5 packs alongside an active subscription |
| Token Plan Team Standard | ¥150/seat (orig ¥198) | not offered | 25,000 Credits/seat/month | Multi-seat management, usage analytics, no training on conversation data |
| Token Plan Team Pro | ¥550/seat (orig ¥698) | not offered | 100,000 Credits/seat/month | Same as Standard |
| Token Plan Team Max | ¥1,398/seat | not offered | 250,000 Credits/seat/month | Same as Standard |
| Team shared bundle | ¥5,000/pack | n/a | 625,000 Credits, 1-month validity | Pool shared across seats |
| Coding Plan Pro | ¥200 (first month ¥39.90) | not offered | 6,000 requests/5hr, 45,000/week, 90,000/month | Per-request billing; simple tasks 5-10 model calls, complex 10-30+; limited daily inventory restocked 09:30 (UTC+8) |
Terms explained:
- Concurrent agents - newly documented this month: Personal plans cap simultaneously running agents (1-2 on Lite up to 6-8 on Pro), the first hard concurrency disclosure on any Alibaba plan. Source: Alibaba – Token Plan Overview
- No training on team data - the Team edition "commits to not using data to train models"; the Coding Plan instead grants Alibaba a license to use inputs/outputs for service improvement during the subscription, and prohibits API/automated usage. Sources: Alibaba – Token Plan Overview , Alibaba – Coding Plan
- Credits formula - only plan-level Credit totals are published; per-model Credit consumption rates remain undisclosed. Source: Alibaba – Token Plan Overview
Source: Alibaba – Token Plan Overview , Alibaba – Coding Plan
API Pricing
All prices CNY per million tokens, China mainland Beijing region, with approximate USD at $1 = ¥7.2. Public pages show original prices only; active promos live in the console (exception: qwen3.7-plus inline discount).
Qwen3.8 family (coding-relevant current generation)
| Model | Context tier | Input (¥/MTok) | Output (¥/MTok) | Input (USD) | Output (USD) | Batch / cache | Free quota |
|---|---|---|---|---|---|---|---|
| qwen3.8-max-prime | 0-1M | 24 | 72 | ~$3.33 | ~$10.00 | Cache discount; 1.5-2x TPS | None |
| qwen3.8-max (= 0902) | 0-1M | 12 | 36 | ~$1.67 | ~$5.00 | Batch 50%; cache discount | 1M tokens, 90 days |
| qwen3.8-max-0902 | 0-1M | 12 | 36 | ~$1.67 | ~$5.00 | Cache discount | 1M tokens, 90 days |
| qwen3.8-2.4t-a95b (open weights) | 0-1M | 12 | 36 | ~$1.67 | ~$5.00 | Cache discount | 1M tokens, 90 days |
| qwen3.8-27b (open weights, dense) | 0-1M | 3 | 12 | ~$0.42 | ~$1.67 | Cache discount | 1M tokens, 90 days |
| qwen3.8-flash (multimodal) | 0-1M (flat) | 0.8 | 2.7 | ~$0.11 | ~$0.38 | Cache discount | 1M tokens, 90 days |
Qwen3.7 generation (still sold)
| Model | Context tier | Input (¥/MTok) | Output (¥/MTok) | Notes |
|---|---|---|---|---|
| qwen3.7-max (= 2026-05-20) | 0-1M | 12 | 36 | Batch 50%; cache discount |
| qwen3.7-plus (alias) | 0-256K | 1.6 (promo; orig 2) | 6.4 (promo; orig 8) | Limited-time 20% discount, no end date |
| qwen3.7-plus (alias) | 256K-1M | 4.8 (promo; orig 6) | 19.2 (promo; orig 24) | Same promo |
| qwen3.7-flash | 0-32K | 0.2 | 0.8 | Also 0.6/2.4 (32-256K), 1.2/4.8 (256K-1M) |
| qwen3.6-plus | 0-256K | 2 | 12 | 8/48 at 256K-1M |
| qwen3.6-flash | 0-256K | 1.2 | 7.2 | 4.8/28.8 at 256K-1M |
Legacy qwen3-coder-plus and qwen3-coder-flash remain listed on the billing page; qwen3-coder-next remains on the Coding Plan list. Context caching rules: explicit cache creation bills at 125% of input price, cache hits at 10%; input prices above exclude cache rates.
Regional pricing (qwen3.8-max and 0902 snapshot)
| Region | Scope | Input (¥/MTok) | Output (¥/MTok) |
|---|---|---|---|
| Beijing (China mainland) | n/a | 12 | 36 |
| US (Virginia) | Global | 12 | 36 |
| Germany (Frankfurt) | Global | 12 | 36 |
| Japan (Tokyo) | Global | 12 | 36 |
| Singapore | International | 14.988 | 44.965 |
Singapore international rates for the open-weight models: qwen3.8-2.4t-a95b ¥14.988/¥44.965; qwen3.8-27b ¥3.646/¥21.875.
Source: Alibaba – Billing For Model Studio
Model Performance / Benchmarks
Alibaba publishes no SWE-Bench Verified, Terminal-Bench, or LiveCodeBench scores for the closed qwen3.8-max flagship; the August "autonomous coding for dozens of consecutive days" claim still has no methodology. The only first-party numbers published are for the open-weight flagship on its release note, plus third-party scores:
| Model | Benchmark | Score | Source type |
|---|---|---|---|
| qwen3.8-2.4t-a95b | GPQA Diamond | 92.6 | Alibaba release note |
| qwen3.8-2.4t-a95b | PaperBench | 93.0 | Alibaba release note |
| qwen3.8-2.4t-a95b | OSWorld | 86.1 | Alibaba release note |
| qwen3.8-2.4t-a95b | BabyVision | 82.0 | Alibaba release note |
| qwen3.8-2.4t-a95b | CodeArena | Global #4 | Alibaba release note |
| qwen3.8-27b | Artificial Analysis Intelligence Index | 52 | Third-party (Artificial Analysis) |
The 27B score was widely discussed on HackerNews (381 points): News – Item Community quantization testing found 4-bit Qwen3.8-27B holds capability while 1-bit collapses: Quesma – Qwen38 27B Quantizations Benchmarked . Sources: Alibaba – Newly Released Models , Artificialanalysis – Qwen3 8 27B
Latest News
qwen3.8-max-0902 Snapshot (September 2, 2026)
New dated snapshot of the 2.4T flagship: deeper coding for engineering-grade projects and long-horizon autonomous development, improved collaborative-agent multi-tool orchestration, sharper vision/chart reasoning; keeps 1M context, thinking mode, and full tool ecosystem at ¥12/¥36. Source: Alibaba – Newly Released Models
Retrieval Models Refresh (September 1, 2026)
qwen3.7-text-rerank (large gains in general/web/code/instruction/agentic/memory retrieval, websearch +~35% vs qwen3-rerank) and qwen3.7-text-embedding-flash (201 languages, 32K to 128K documents, sparse embedding) shipped, relevant to coding agents that rely on repository retrieval. Source: Alibaba – Newly Released Models
qwen3.8-omni-flash and Realtime Variant (September 17 / 21, 2026)
Omni-flash: text/image/audio/video in, text out, thinking modes, function calling, web search, context caching. The realtime variant adds multi-channel audio/video aggregation and remote MCP tool calling over WebSocket, WebRTC, and AOQ, Alibaba's first Bailian model exposing remote MCP in a realtime API. Sources: Alibaba – Newly Released Models , News – Item
Marketplace Wave: DeepSeek V4.1 Flash, GLM-5.3-FlashX, Step-5 Preview (September 13-21, 2026)
DeepSeek-V4.1-Flash (552B MoE, causal encoder-decoder, 1M context, 384K output, KV cache at 1/4 of prior HBM size), Zhipu GLM-5.3-FlashX at 200 tokens/s, and StepFun Step-5-Preview (600B/27B active, 1M context, agentic-coding flagship strong in finance) all landed on Bailian within eight days. Source: Alibaba – Newly Released Models
qwen3.8-max-prime Listed (September, exact date undisclosed)
A Prime (优速) tier of the flagship appeared on the billing page at ¥24/¥72 per MTok, no free quota; Prime mode targets output-speed-sensitive workloads (coding assistants, multi-step agents) with 1.5-2x TPS. Sources: Alibaba – Billing For Model Studio , Alibaba – Prime Mode
Anthropic Distillation Report and US Accusations (September 10 / 13, 2026)
Anthropic's threat-intelligence update detailed coordinated distillation campaigns attributed to Alibaba; days later, US agencies publicly accused top Chinese AI developers including Alibaba of systematically copying American models. Both raise compliance and reputational considerations for Western buyers of Qwen APIs. Sources: TechCrunch – Anthropic Details Distillation Campaigns From Alibaba Moonshot Ai And Deepseek , Nbcnews – Us Accuses China Ai Developers Deepseek Alibaba Copying American Ai Rcna596696
Qwen3.8-Flash-Next Ecosystem Spillover (late August, shaping September)
Qwen3.8-Flash-Next (125B total, ~6B active, open weights, released August 26) dominated September's local-innovation layer: community projects run the 104GB model on 48GB Macs via SSD streaming (240-point HN thread) and third parties post-trained efficiency variants. Sources: News – Item , News – Item
Community Signals
Qwen3.8-27B on Cerebras at 1,500 tokens/s (691 points, 228 comments)
The highest-engagement Qwen story of September was Cerebras hosting the open-weight 27B dense model at ~1,500 tok/s (versus ~80 tok/s for the fastest OpenRouter provider at the time). Developer experience was mixed on cost and limits. gpugreg: "There is a limit of 450,000 tokens per minute. I hit this limit in about 90 seconds and burned through $1.10 while doing so... I ran the same task with DeepSeek-V4-Flash, which finished in 172 seconds and cost $0.024." News – Item . eli measured real speed: "The p50 speed was 890 tok/s and 0.64s TTFT. Using OpenRouter averages, that would've cost $0.29 (no cache discount at Cerebras!) and would've taken about 14.4 minutes." News – Item . hexa00 on coding quality: "Output is awesome, super fast as you expect from the 1500t/sec... Tool call is failing more than say DS4, which leads to time wasted on retries." News – Item . Context was the recurring blocker; lsb: "The context window is limited to 64k or 128k. If you're using this with a coding agent, there's going to be a lot of compactions." News – Item . Others skipped hosted entirely; walrus01: "I don't see the point of paying for external inference on Qwen 3.8 27B with a bunch of arbitrary limits, when you can run it locally... fits in 64GB." News – Item . Thread: News – Item
Quantization Study: 4-bit Holds, 1-bit Collapses (286 points, 139 comments)
Independent benchmarking of Qwen3.8-27B quantizations found little quality loss down to 4-bit and collapse at 1-bit, driving local-coding adoption advice. KennyBlanken flagged the practical tier: "It's strange that the author has completely ignored the 3 bit quants which allow someone with a 16GB GPU to have 100-120k and still get full performance." News – Item . anyfoo reported a threshold effect on a real coding task: "To my own surprise, Q6_K_XL (from unsloth) comes up with a solution, anything Q5 doesn't." News – Item . bellowsgulch captured the economics vs hosted rivals: "It seems cheaper to me to just use MiMo V2.5 for pennies or DeepSeek V4 Flash instead of using Qwen anymore unless I need a local model specifically." News – Item . nateb2022 explained the structural cost gap: "Generating 1 token through DS4's 13B active params requires roughly half the FLOPs... [versus a dense 27B]." News – Item . Thread: News – Item
Other September Signals
The Qwen3.8 Omni Flash announcement drew 346 points and 138 comments: News – Item . A gist showing Qwen 3.8 following GPT-5.5 Pro reasoning prefills (distillation-style behavior) drew 237 points: News – Item . An independent fine-tune cutting Qwen3.8-27B thinking tokens by 58% with under 1% accuracy loss (LiveCodeBench v6 76.8 to 81.6) reached 80,000 downloads in 3 days: News – Item . Simon Willison's August review of the 27B ("excellent, but it defaults to overthinking", 802 points) continued anchoring the local-model debate: News – Item . Reddit search for Qwen community signals was blocked (login wall) and could not be used this cycle.
Reddit recovery (added 2026-10-03)
r/LocalLLaMA (2.1K upvotes, 566 comments, ~Sep 22): "Qwen 4 Announced at Apsara Conference" Reddit – Qwen 4 Announced At Apsara Conference . Qwen-Image-2.1 drew r/LocalLLaMA (1.9K upvotes, 388 comments) Reddit – Qwenimage21 Released and r/StableDiffusion (1.5K upvotes, 288 comments) Reddit – Qwen Image 21 1Girl Examples . The qwen.ai/research blog became extractable on retry: Qwen3.8-Omni-Flash (Sep 18) is framed for "agentic delivery" with planning, tool calling, and coding-adjacent knowledge work. Alibaba – Research Community scale: r/Qwen_AI 83K weekly visitors.
Enterprise Readiness
| Feature | Available? | Details |
|---|---|---|
| SSO (SAML/OIDC) | Partial | Alibaba Cloud RAM supports SAML SSO for console access; no native OIDC documented for API access. Source: Alibaba – Coding Plan |
| SCIM | No | No SCIM-based provisioning documented; teams add members manually via workspace permission management. Source: Alibaba – Coding Plan |
| Audit logs | Partial | Billing/usage logs via Alibaba Cloud Billing Center; Token Plan teams get per-member usage analytics. Source: Alibaba – Token Plan Overview |
| IP indemnity | No | No IP indemnity documented for Qwen models or Bailian. |
| Data residency | Partial | Pay-as-you-go across Beijing, Singapore, Tokyo, Frankfurt, Virginia; Token Plan and Coding Plan are Beijing-only. Source: Alibaba – Token Plan Overview |
| HIPAA | No | No HIPAA compliance documented. |
| Air-gapped / on-prem | Partial | Custom models can deploy on dedicated instances; no air-gapped hosted-Qwen option. Open weights (qwen3.8-2.4t-a95b, 27b) enable self-hosting. Source: Alibaba – Billing For Model Studio |
| SLA | Undisclosed | No availability/latency SLA in public pricing docs. |
| Admin controls (RBAC) | Yes | RAM role-based control; workspace admin/member roles; per-seat Credit allocation and recall on Token Plan teams. Source: Alibaba – Token Plan Overview |
Terms explained:
- Data residency split - subscriptions process data in Beijing only, so teams with data-localization requirements outside China must use pay-as-you-go regions or self-host the open weights. Source: Alibaba – Token Plan Overview
- Training-data commitments - Token Plan Team promises no training on conversation data; the Coding Plan explicitly licenses inputs/outputs to Alibaba during subscription (Bailian Service Agreement clause 5.2). Source: Alibaba – Coding Plan
Transparency Gaps
| Gap | Details | Severity |
|---|---|---|
| Closed-flagship benchmarks missing | No SWE-Bench, Terminal-Bench, or LiveCodeBench scores for qwen3.8-max or the 0902 snapshot; the "dozens of consecutive days" autonomous-coding claim (August) still has no methodology. | High |
| Credits formula undisclosed | Per-model Credit consumption rates for Token Plan are unpublished; only plan totals (11,500 to 250,000 Credits) are visible. | High |
| Rate limits undisclosed | Pay-as-you-go RPM/TPM limits are not on the pricing page; community reports cite third-party limits (e.g., Cerebras 450K TPM), not Alibaba's own. | High |
| Coding Plan data-use scope | The plan licenses inputs/outputs to Alibaba and bans API/automated use, but retention scope and post-termination use of already-licensed data are unspecified. | High |
| Prime tier documentation lag | qwen3.8-max-prime (¥24/¥72) is billed on the pricing page but absent from the Prime-mode supported-models table; no release date, no cache-hit price, no free quota. | Medium |
| Promo end dates undisclosed | No end dates for Token Plan limited-time prices (¥39/79/139/499, ¥150/550 team) or the qwen3.7-plus 20% discount. | Medium |
| Open-weight license terms | The qwen3.8-2.4t-a95b release note still does not state license terms on the Bailian page. | Medium |
| qwen.ai blog inaccessible | The old blog redirects to qwen.ai/research, which is JS-rendered and yielded no extractable September posts via standard fetch or browser automation; release facts rely on Aliyun docs. | Medium |
| SLA undocumented | No availability, latency, or error-rate SLA in public documentation. | Medium |
| Singapore premium unexplained | qwen3.8-max international pricing (¥14.988/¥44.965) runs ~25% above Beijing with no documented rationale (though below qwen3.7-max international at ¥18.736/¥56.207). | Low |