Qwen3.8 Max: specs, benchmarks, pricing & API options — now live in the Flagship Pool
Qwen3.8 Max (also written “Qwen 3.8 Max”; API id qwen3.8-max) is Alibaba’s flagship model, announced July 19: a 2.4-trillion-parameter system with a 1M-token context window, scoring 58 on the independent Artificial Analysis Intelligence Index (v4.1.1) — top-five territory, two points behind Kimi K3 (60), the current open-weights ceiling. As we chart below, that score at Qwen’s list price lands it on the price-vs-intelligence Pareto frontier — and knocks Claude Sonnet 5 off it.
Update, August 14, 2026: the review is over — Qwen3.8 Max is live in our Flagship Pool. Alibaba shipped the open-weight variant on August 13, the licensing gate we describe below lifted, and every Flagship subscriber can now call it with model id qwen3.8-max — unlimited, flat-rate, from $199/mo, next to Kimi K3. Setup, specs and examples: Qwen3.8 Max API — pricing, access & subscription.
curl https://api.cheapestinference.com/v1/chat/completions \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{"model": "qwen3.8-max", "messages": [{"role": "user", "content": "Hello"}]}'The analysis below is the review that got it there, kept as published (August 4) with the status lines updated.
Qwen3.8 Max specs and benchmarks
Section titled “Qwen3.8 Max specs and benchmarks”| Architecture | ~2.4T total parameters (MoE details unpublished) |
| Context window | 1M tokens |
| Open weights | Released August 13, 2026 — Qwen3.8-2.4T-A95B, the open variant of the Max |
| Vision | Yes — image input |
| List price (API) | $2 input / $6 output per 1M tokens (cached input from $0.25) |
The benchmark picture: 58 on the Artificial Analysis index (v4.1.1) puts Qwen3.8 Max above every previous Qwen release and within two points of Kimi K3 (60). Independent benchmarking is ongoing; active-parameter counts and MoE configuration haven’t been published, so per-token compute cost can’t be derived yet.
Qwen3.8 Max vs Kimi K3
Section titled “Qwen3.8 Max vs Kimi K3”The head-to-head everyone is asking for — the two highest-scoring models in the open(-ing) ecosystem, and on paper they’re complements rather than rivals:
| Qwen3.8 Max | Kimi K3 | |
|---|---|---|
| AA Intelligence Index | 58 | 60 |
| Parameters | ~2.4T (MoE, config unpublished) | ~2.8T MoE |
| Context window | 1M tokens | 1M tokens |
| List price (in / out per 1M) | $2.00 / $6.00 | $3.00 / $15.00 |
| Open weights | Published August 13, 2026 (2.4T-A95B) | Published July 27, 2026 |
| Status here | Live in the Flagship Pool since August 14 | Live in the Flagship Pool |
K3 holds the intelligence crown and the agentic-coding pedigree; Qwen3.8 Max answers with 2.5× cheaper output at two index points’ distance, plus standard sampling controls. One pool serving both covers the two profiles that matter — peak agentic reasoning and tunable long-context breadth — which is exactly what the Flagship Pool now does.
Qwen3.8 Max on the price-vs-intelligence Pareto frontier
Section titled “Qwen3.8 Max on the price-vs-intelligence Pareto frontier”A model is on the frontier when nothing tracked is both smarter and cheaper. At index 58 for a $6.00/1M list output price, Qwen3.8 Max steps onto the frontier — five points above Claude Sonnet 5 at 40% lower list price — and pushes Sonnet 5 off it:
Four of the five models on that frontier — V4-Flash-0731, GLM 5.2, Qwen3.8 Max and Kimi K3 — are served here on flat rate. The monthly-updated, full-field version of this chart (with cost-per-task data and edition history) lives in our LLM Pareto Frontier report.
What gated the decision — and how it resolved
Section titled “What gated the decision — and how it resolved”When this review was published (August 4), Qwen3.8 Max had no open weights and no open license. Qwen’s open releases (3.5, 3.6) shipped under Apache 2.0; its Max tier had historically stayed closed — a tension the community debated openly since the preview shipped. Our review status was explicit that licensing, not quality, was the gate.
On August 13 Alibaba resolved it: Qwen3.8-2.4T-A95B — the open-weight variant of the Max — shipped on Hugging Face and ModelScope, followed on August 14 by the dense Qwen3.8-27B under Apache 2.0. The final scorecard:
- Quality — reviewed on real agent workloads through both our OpenAI and Anthropic endpoints, including tool calling: ✅ passed.
- Fit — a second flagship-class model with a different profile (hybrid reasoning, standard sampling, 1M context, vision) next to Kimi K3: ✅ strong.
- Licensing — ✅ open weights published August 13.
Result: live in the Flagship Pool on August 14 — the pipeline’s fastest gate-to-launch turnaround so far. The models-under-review board and the changelog reflect it.
Common questions
Section titled “Common questions”Is there an unlimited Qwen3.8 Max API?
Yes — live since August 14, 2026: the CheapestInference Flagship Pool serves Qwen3.8 Max with no token caps during your reserved hours, from $199/month for a daily 8-hour block, on the same subscription as Kimi K3. Model id qwen3.8-max; setup on the model page. Seats are very limited.
Does Qwen3.8 Max have open weights? Yes, as of August 13, 2026: Alibaba published Qwen3.8-2.4T-A95B, the open-weight variant of the Max, on Hugging Face and ModelScope — and the dense Qwen3.8-27B followed on August 14 under Apache 2.0.
How much does the Qwen3.8 Max API cost? Per token, list price is $2.00 per 1M input tokens and $6.00 per 1M output, with cached input from $0.25 — a 100M-token month lands around $200–600 depending on cache-hit rate and output mix. The credit-based subscription plans we analyzed in Qwen coding plans, explained cap usage per 5-hour and 7-day windows. For heavy use, our flat-rate unlimited route starts at $199/month.
What is the context window of Qwen3.8 Max? 1M tokens, per Alibaba’s published spec for the model.
CheapestInference serves Kimi K3 and Qwen3.8 Max (Flagship Pool), GLM 5.3 and MiniMax M3 (Frontier Pool) and DeepSeek V4.1 Flash and MiMo v2.5 (Core Pool) through one OpenAI- and Anthropic-compatible API on unlimited time-block subscriptions. See the pools or get started.