Qwen3.5 397B A17B vs Claude Opus 4.5
At a Glance
| Compare | Claude Opus 4.5Anthropic | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #27 of 4655.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 36.9–70.3 |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #40 of 44$0.380 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #36 of 3838.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 28.8–45.4 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.45Deepinfra ↗ · Sep 21, 2026 | $5.00Anthropic ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $3.00Deepinfra ↗ · Sep 21, 2026 | $25.00Anthropic ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 262K | 200K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 3, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | Qwen3.5-397B-A17B | Claude Opus 4.5 |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,438.2699% of row best · rating · qwen3.5-397b-a17b; 95% CI [1434.97391785, 1441.55191176]; votes 77007; rank 71 | 1,447.08100% of row best · rating · claude-opus-4-5-20251101-high-32k; 95% CI [1443.17965746, 1450.98398333]; votes 36239; rank 49 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 1 benchmark winNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Qwen3.5-397B-A17B | Claude Opus 4.5 |
|---|---|---|
| Developer | Qwen | Anthropic |
| Family | Qwen3 5 397b A17b | Claude 4 |
| Model | Qwen3.5-397B-A17B | Claude Opus 4.5 |
| Version | Qwen3.5-397B-A17B | Claude Opus 4.5 |
| Lifecycle | active | active |
| Released | 2026-02-15 | 2025-11-24 |
| Knowledge cutoff | Unknown | 2025-05-01 |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 262K | 200K |
| Total parameters | 403.4B | Unknown |
| Active parameters | 17B | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Anthropic (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, structured_outputs, tools |
Qwen3.5 397B A17B Capabilities
Claude Opus 4.5 Capabilities
Related Comparisons
All image comparisons →| A | Pair | B | Context |
|---|---|---|---|
| vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text | |
| vs | Claude Fable 5.1Anthropic | cross-developer peersimage, text | |
| vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext | |
| vs |  DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text | |
| vs | Grok 4.6xAI | cross-developer peersimage, text | |
| vs |  Qwen3.8-MaxQwen | family variantsimage, text | |
| vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text | |
 MiniMax-M3MiniMax | vs | cross-developer peersimage, text | |
| vs |  GLM-5.3Z.ai | cross-developer peerstext | |
| vs |  Hy4 previewTencent | cross-developer peerstext | |
| vs | Seed 2.1 ProByteDance Seed | cross-developer peersimage, text | |
| vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Qwen3.5 397B A17B vs Claude Opus 4.5 FAQs
Is Qwen3.5 397B A17B or Claude Opus 4.5 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.5 397B A17B and Claude Opus 4.5, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Qwen3.5 397B A17B or Claude Opus 4.5?+
Qwen3.5 397B A17B is $0.45 and Claude Opus 4.5 is $5.00 per million tokens, so Qwen3.5 397B A17B is cheaper on this metric. Qwen3.5 397B A17B is $3.00 and Claude Opus 4.5 is $25.00 per million tokens, so Qwen3.5 397B A17B is cheaper on this metric.
Which has a larger context window, Qwen3.5 397B A17B or Claude Opus 4.5?+
Qwen3.5 397B A17B has the larger sourced context window. Qwen3.5 397B A17B supports 262K and Claude Opus 4.5 supports 200K.
Which performs better in benchmarks, Qwen3.5 397B A17B or Claude Opus 4.5?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Qwen3.5 397B A17B or Claude Opus 4.5 be self-hosted?+
Qwen3.5 397B A17B is the only model in this pair currently marked as self-hostable. Qwen3.5 397B A17B is open weight; Claude Opus 4.5 is not marked open weight.
Can Qwen3.5 397B A17B and Claude Opus 4.5 understand images?+
Qwen3.5 397B A17B is documented with image input; Claude Opus 4.5 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Qwen3.5 397B A17B or Claude Opus 4.5?+
Neither has a larger sourced maximum output. Qwen3.5 397B A17B is — and Claude Opus 4.5 is 64K.
Do Qwen3.5 397B A17B and Claude Opus 4.5 support reasoning and tool use?+
Qwen3.5 397B A17B: reasoning, tool calling, and image input. Claude Opus 4.5: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Qwen3.5 397B A17B or Claude Opus 4.5?+
Qwen3.5 397B A17B has 4 sourced provider routes; Claude Opus 4.5 has 1, so Qwen3.5 397B A17B has broader tracked availability.
Which offers better value, Qwen3.5 397B A17B or Claude Opus 4.5?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.