Qwen 4 vs Claude Opus 5.5: Specs, Speed & Pricing

1M Context and 58 Intelligence Score: Comparing Qwen 4 and Claude Opus 5.5

Claude Opus 5.5 delivers a verified production cloud tier scoring 58 on the Artificial Analysis Intelligence Index with 95.2 output tokens per second, while Qwen 4 targets local deployment and hybrid sparse-attention efficiency across a 1,000,000-token window — the right pick depends on whether your system requires an active, managed API or an upcoming open-weight foundation. Claude Opus 5.5 has been generally available since September 22, 2026, giving engineering teams an established SLA, native multimodal support, and published pricing. Qwen 4, by contrast, is actively in training at Alibaba Cloud, with its structural innovations previewed through open experimental checkpoints and community evaluation canaries.

Key Takeaways

• Commercial Availability vs. Pre-Release Engineering: Claude Opus 5.5 is fully deployed in production with documented API pricing ($4.00 input, $20.00 output per 1M tokens). Qwen 4 is officially confirmed in training, with no public weights or commercial API rates live.
• Benchmark Realities: Claude Opus 5.5 holds the top spot on the Artificial Analysis Intelligence Index with a score of 58 out of 132 models. Qwen 4 has no verified vendor benchmarks, though early canary testing under the alias "Kalmia" shows competitive results in frontend and 3D tasks.
• Context Capacity: Both models target a 1,000,000-token (1M) context window. Claude Opus 5.5 pairs this with up to 128,000 output tokens, while Qwen 4 commits code defaults of 1M tokens across its planned family.
• Architectural Profiles: Claude Opus 5.5 operates as a closed frontier cloud service with dedicated fast inference modes. Qwen 4 relies on a hybrid linear/sparse attention design, gated residual streams, and memory-offloaded n-gram tables.
• Hardware Footprint: Qwen 4 includes a planned open-weight 27B variant intended for consumer GPUs, while Claude Opus 5.5 requires Anthropic's hosted infrastructure.

Qwen 4 vs Claude Opus 5.5 at a Glance

Evaluation Dimension	Claude Opus 5.5	Qwen 4 (Family)	Source Verification
Release Status	Generally Available (Sep 22, 2026)	In Training (Confirmed Sep 22, 2026)	Vendor announcements
Developer / Provider	Anthropic	Alibaba Cloud	Official platforms
Deployment Model	Closed API / Managed Cloud	Cloud API + Open Weights (Planned)	Official roadmap / Leaks
Context Window	1,000,000 tokens (128k output)	1,000,000 tokens (Repository default)	API spec / GitHub PR #15762
Standard Pricing (1M Tokens)	$4.00 Input / $20.00 Output	unverified — no public number yet	Anthropic docs / Alibaba unreleased
Fast Mode Pricing (1M Tokens)	$8.00 Input / $40.00 Output	Not applicable	Anthropic service card
Measured Output Speed	95.2 tokens/second (Standard)	unverified — no public number yet	Artificial Analysis independent test
Intelligence Index Score	58 (Rank #1 of 132 models)	unverified — no public number yet	Artificial Analysis benchmark board
Core Architecture	Proprietary Multimodal Foundation	Sparse MoE + Hybrid Attention + PLE	Model card previews / Commits

Architecture and System Footprint

The architectural contrast between these two systems reflects distinct philosophies regarding memory bandwidth and hardware accessibility. Claude Opus 5.5 represents Anthropic's flagship dense cloud deployment. It accepts text, images, and files natively, operating behind a managed endpoint designed to sustain high output token velocity without exposing infrastructure burdens to end users. On October 15, 2026, Anthropic expanded this cloud footprint by transitioning its fast mode out of preview, providing up to 2.5 times the output speed for developers willing to pay a 100% price premium.

Qwen 4 takes an architectural path designed to decouple compute from sequence memorization. Alibaba's preliminary model, Qwen3.8-Flash-Next—released on August 24, 2026—served as an explicit technical preview for the upcoming Qwen 4 family. That preview outlined a sparse Mixture-of-Experts (MoE) configuration totaling 125B parameters, but activating only 6B parameters per token.

+-------------------------------------------------------------------+
|                        Qwen 4 Preview Stack                       |
+-------------------------------------------------------------------+
|  Active Layer:  6B parameters active per token (from 125B MoE)    |
|  Hybrid Core:   Gated DeltaNet + Qwen Sparse Attention (QSA)      |
|  Memory Table:  51B Parameter-Free Lookup Embedding (PLE in RAM)  |
|  Training:      Muon + AdamW optimizers with RSI pipelines        |
+-------------------------------------------------------------------+

This design combines Gated DeltaNet with a custom Qwen Sparse Attention (QSA) mechanism, which processes sequence blocks rather than single tokens to mitigate latency over long contexts. To scale model capacity without inflating compute requirements, Qwen 4 integrates a 51B-parameter Parameter-Free Lookup Embedding (PLE) layer. This n-gram table offloads phrase recall directly into system DDR memory, allowing workstations with limited VRAM to run inference efficiently.

Source: @MaxForAI

At the annual Apsara Conference in Hangzhou, Max For AI reported from the Apsara keynote that Alibaba LLM leadership officially confirmed four distinct tiers: Qwen4-Max, Qwen4-Plus, Qwen4-Flash, and Qwen4-27B. On the infrastructure side, Alibaba is aligning this training workload with its in-house T-Head Zhenwu V900 silicon, designed with 216GB of high-bandwidth memory and 1,200 GB/s interconnects for clusters supporting up to 500,000 chips. Where Opus 5.5 optimizes for centralized datacenter throughput, the Qwen 4 architecture shifts parameter scale into system RAM via offloaded lookup tables to keep per-token activation under 6B parameters. For a broader structural breakdown of this approach, read What the Qwen 4 Architecture Shift Means for Open-Weight Engineering.

Benchmark Signals and Coding Capability

Comparing real-world performance requires evaluating Claude Opus 5.5's verified metrics alongside the unconfirmed community tests currently circulating for Qwen 4.

Claude Opus 5.5 is the current reference point for complex reasoning and agentic workflows. On the independent Artificial Analysis Intelligence Index, Opus 5.5 scores 58 at maximum effort, ranking first across 132 evaluated models. In production engineering environments, developers rely on Opus 5.5 for multi-file repository maintenance, intricate refactoring, and deterministic tool use. Its standard output rate of 95.2 tokens per second makes it practical for conversational agents and high-throughput production backends.

Because Qwen 4 has not officially launched, it lacks official benchmark scores. However, Alibaba revealed that its entire Qwen 4 lineup is trained using Recursive Self-Improvement (RSI). When Alibaba applied RSI to its prior Qwen 3.8 Max model over a 30-day baseline test, the model's score on the Artificial Analysis Intelligence Index increased from 40 to 45. Engineering estimates suggest applying this technique alongside the Muon Optimizer across Qwen 4's four tiers aims to narrow the gap with closed frontier leaders.

In evaluation environments, community researchers have tracked several unidentified models widely suspected to be Qwen 4 checkpoints operating under the canary alias "Kalmia" and later "Kerria".

+--------------------------------------------------------------------+
|               Observed Blind Arena & Canary Signals                |
+--------------------------------------------------------------------+
|  "Kalmia" Canary:   High-density Three.js webdev & 3D voxel scenes |
|  Canary vs Sonnet:  23,750 blocks (Kalmia) vs 44,107 blocks (Sonnet)|
|  Canary vs Astra:   32 min generation (Kerria) vs 49 min (Astra)   |
|  RSI Progression:   Qwen 3.8 Max baseline jumped 40 -> 45 index    |
+--------------------------------------------------------------------+

Blind arena testers observed "Kalmia" producing complex interactive code, such as full Three.js scene graphs and browser-based games generated from scratch in under 20 minutes. Community evaluator Lumina logged arena web development runs, noting competitive functional outputs. However, comparative quality remains variable across tasks:

• Spatial Reasoning and Construction: In a direct comparison using an identical Minecraft construction prompt, the Kalmia checkpoint placed 23,750 blocks, compared to 44,107 blocks placed by Claude Sonnet 5.5. The evaluator noted Sonnet demonstrated significantly higher structural polish.
• Rendering Throughput: In a Three.js street-market visual test, the Kerria canary completed its output generation in 32 minutes, outperforming GPT-6 Astra's 49-minute runtime, though Astra produced cleaner interactivity.
• 3D Domain Evaluation: On October 23, 2026, Alibaba open-sourced BlenderWorld, a specialized benchmark containing 223 tasks and 2,651 binary criteria evaluating visual agents generating 3D assets in Blender. The benchmark release aligns with the visual and spatial proficiencies observed in early Qwen 4 test outputs.

Early signal indicates Qwen 4 achieves parity with frontier models on targeted code generation, but head-to-head empirical data across comprehensive reasoning benchmarks remains unverified. For developers evaluating other frontier comparisons, see our analysis in Head-to-Head: GPT-6.2 Astra and Opus 5.5 on Code Execution and $4/$20 Token Pricing.

Context Limits, Reasoning Controls, and Pricing Realities

Context handling and runtime configuration highlight the diverging economics of managed closed-source APIs versus locally deployable systems.

Anthropic offers Claude Opus 5.5 with a fully verified 1,000,000-token context window capable of generating up to 128,000 output tokens in a single request. Its pricing structure is fixed:

• Standard Mode: $4.00 per million input tokens, $20.00 per million output tokens.
• Fast Mode: $8.00 per million input tokens, $40.00 per million output tokens.

This structure allows organizations to forecast operating costs based on predictable token billing. Teams integrating production pipelines can explore hosted models like Claude Opus 5.5 directly via managed cloud endpoints to maintain stable latency.

For Qwen 4, official pricing and hosting tiers remain unannounced. Predecessor pricing for Qwen 3.8 Max sits at $2.00 per million input tokens and $6.00 per million output tokens on Alibaba Cloud Model Studio. Pre-release signals confirm that Qwen 4 is engineered around large-context workflows. In late October 2026, the open-source client codebase merged PR #15762, formally sizing the default context window at 1,000,000 tokens for the entire generation, including qwen4, qwen4-max, qwen4-plus, and qwen4-coder-plus.

Source: @ItsmeAjayKV

As community researcher AJ tracked the commit, the merged PR #15762 raised token limits across the lineup to prevent early context compaction. Subsequent client updates added discrete DashScope reasoning controls (none, low, medium, and xhigh, with xhigh configured as the default). Anthropic charges an observable premium for deterministic speed, while Alibaba's architectural investments focus on reducing raw compute costs through hardware offloading and sparse routing.

Which One Should You Use?

Choosing between these two models involves balancing immediate production stability against architectural independence.

Choose Claude Opus 5.5 if:

• Your product demands verified state-of-the-art reasoning: Opus 5.5 holds a confirmed score of 58 on the Artificial Analysis Index, offering superior stability for complex automated decision pipelines.
• You need immediate enterprise SLAs: Anthropic provides published service cards, contractual data privacy guarantees, and deterministic cloud performance without internal hardware overhead.
• Your workflows depend on high-volume output generation: With support for up to 128,000 output tokens and an optional 2.5x fast mode, Opus 5.5 is purpose-built for large-scale document and code synthesis.

Choose Qwen 4 if:

• You require local or air-gapped deployment: The upcoming Qwen4-27B tier is tailored for on-premise inference on standard hardware like the RTX 3090, eliminating third-party API dependencies.
• You want to avoid variable per-token API costs: Running open-weight quantized builds on dedicated hardware enables continuous offline processing, batch jobs, and local agent development at fixed compute costs.
• You are building workflows around sparse memory architectures: Qwen 4's integration of RAM-offloaded n-gram tables and hybrid attention offers distinct advantages for developers experimenting with customized inference engines.

Frequently Asked Questions

Is Qwen 4 better than Claude Opus 5.5?

Independent evaluations rank Claude Opus 5.5 first overall with a verified score of 58 on the Artificial Analysis Intelligence Index, whereas Qwen 4 remains unreleased with only unconfirmed canary tests pointing to competitive reasoning on select coding tasks. Claude Opus 5.5 remains the verified benchmark leader for production workflows.

Is Qwen 4 cheaper than Claude Opus 5.5?

Alibaba has not published commercial API pricing for Qwen 4, making a direct cost comparison unverified, while Claude Opus 5.5 charges a published rate of $4.00 per million input tokens and $20.00 per million output tokens. Predecessor models such as Qwen 3.8 Max debuted at $2.00 input and $6.00 output per million tokens, indicating future hosted tiers may undercut closed cloud rates.

Can Qwen 4 run locally on consumer hardware?

Alibaba previewed an open-weight Qwen4-27B tier and architecture offloading techniques designed for local inference, whereas Claude Opus 5.5 is strictly a closed proprietary cloud model available only via API. Experimental runtimes utilizing Q4 quantization and PLE memory offloading allow earlier architecture previews to run on workstations equipped with 24GB of VRAM and system DDR memory.

What is the context window for Qwen 4 compared to Claude Opus 5.5?

Both models target a 1,000,000-token context window; Claude Opus 5.5 supports up to 128,000 output tokens on its production endpoint, while Qwen 4 specifies 1M tokens as its default setting in merged repository commits. Production support for the full 1M window is live on Claude Opus 5.5 today, whereas Qwen 4 context behavior remains tied to pre-release code configurations.

Has Qwen 4 officially launched?

No, Alibaba confirmed on September 22, 2026, that Qwen 4 is actively in training, but no official weights, API endpoints, or model cards have been released to the public as of November 2026. Teasers released by Alibaba Cloud—including a November 6 Zhuangzi-themed post—indicate release preparations, but official repositories remain unpopulated.

How do the coding capabilities of Qwen 4 compare to Claude Opus 5.5?

Claude Opus 5.5 is an established benchmark leader for complex agentic software engineering, while early testing of Qwen 4 under arena aliases demonstrates strong 3D scene generation and web development but mixed results against Western frontier models on multi-step reasoning. In specific community tests, Claude models placed nearly double the structural assets on complex construction benchmarks, while Qwen 4 demonstrated faster initial generation on standalone WebGL demos.

What to watch next: track the release of official model weights on Hugging Face, monitor the publication of DashScope commercial API pricing schedules, and follow independent verification on the Artificial Analysis leaderboard once Qwen4-Max completes official post-training.

Try related models on Kie.ai: Claude Opus 5.5, Claude Sonnet 5.5 and Kimi K3.1 Pro.