Qwen3.5 122B-A10B vs Claude Opus 5.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Qwen3.5 122B-A10B by Alibaba against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.
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Live comparison: no in-depth editorial review has been published for this pair yet.
Qwen3.5 122B-A10B
VLM abiertoequilibrado abierto multimodal MoE modelo desarrollado para alto-rendimiento visual comprensión con solo 10B activo parámetros.
$0.00 / 1M
$0.00 / 1M
262.1K tokens
N/A
Claude Opus 5.5
Titán de inteligencia de fronterade Anthropic pinnacle modelo de frontera diseñado para de largo alcance agentic ingeniería de software, denso multimodal documento síntesis, y autónomo investigación flujos de trabajo.
$4.00 / 1M
$20.00 / 1M
1M tokens
84.6%
Diferencias Clave de un Vistazo
- Qwen3.5 122B-A10B is 1.0x cheaper for API usage (input + output tokens combined).
- Claude Opus 5.5 has a larger context window (1M vs 262K tokens).
- Claude Opus 5.5 is faster at 78 tok/s vs 78 tok/s.
| Característica | Qwen3.5 122B-A10B | Claude Opus 5.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 82 | 94 |
Provider | Alibaba | Anthropic |
Input Price Cost per million input tokens | $0.00 / 1M | $4.00 / 1M |
Output Price Cost per million output tokens | $0.00 / 1M | $20.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.00 / 1M | $3.08 / 1M |
Context Window Maximum input + output tokens | 262.1K tokens~393 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 16K | 128K |
Throughput Speed Tokens generated per second | 78 tok/s | 78 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 84.6% |
GPQA Diamond Graduate-level reasoning | 65.5% | 82.3% |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $0.40 / 1M |
¿Quién gana en cada área?
At-a-glance decision frameworkEvaluations ongoing
Puntuaciones de Benchmarks Verificadas
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latencia y Tiempo de Respuesta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interactivo de Costos de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Qwen3.5 122B-A10B · Strengths & Key Advantages
- Feasible un deploy en dual-GPU systems (2x RTX 6000 Ada o 2x A100)
- sólido visual fundamentación y multiturno documento parsing
- de pesos abiertos con comprehensive llamada un herramientas y JSON modo
Considerations & Trade-offs
- menor theoretical profundidad que el 397B insignia sibling
- Occasional minor formateo slips en deeply nested JSON schemas
Claude Opus 5.5 · Strengths & Key Advantages
- inigualable autónomo multipaso codificación agéntica y refactorización
- Flawless multidocumento razonamiento sobre 1M token contexto con no largo-prompt surcharge
- más alto Artificial análisis inteligencia Index ever measured (58/100), leading SWE-bench Pro un 89.9%
- Precise herramienta ejecución con robust error-recovery bucles
Considerations & Trade-offs
- Premium salida precios ($20.00/M) plus heavy razonamiento-token usage (~119K salida tokens por index tarea) keeps largo agentic se ejecuta expensive
- largo pensamiento times un maximum effort puede push un único hard agentic tarea toward ~$13
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Qwen3.5 122B-A10B | Claude Opus 5.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.00 | $3.85 |
Output Tokens / Task Tokens generated per task | 18K | 68K |
Reasoning Tokens / Task Thinking tokens burned per task | 5K | 42K |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | Qwen3.5 122B-A10B | Claude Opus 5.5 |
|---|---|---|
| Official API Model ID (SDK) | qwen3-5-122b-a10b-instruct | claude-opus-5-5-20260901 |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2026-02 | 2026-09 |
| Knowledge Cutoff | December 2025 | June 2026 |
| Architecture | Efficient Open Multimodal MoE Transformer | Extended Autonomous Hybrid Reasoning Transformer |
| Parameters | 122B total (10B active MoE) | Confidential |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Free across full context window (only KV-cache VRAM scales) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Automatic prefix KV-caching in vLLM / SGLang (0 cost) | $0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Native Web Search Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Custom Model Tuning via Amazon Bedrock & Prompt Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 76 GB VRAM (4-bit Quantized) · 262 GB VRAM (Native BF16) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text, vision |
| Output Modalities | text | text |
Qwen3.5 122B-A10B vs Claude Opus 5.5: Respuestas Rápidas (FAQ)
Which is more intelligent, Qwen3.5 122B-A10B or Claude Opus 5.5?
Claude Opus 5.5 is more intelligent. It scores 94 compared with 82 on the composite Intelligence Index.
Which model is cheaper to run?
Qwen3.5 122B-A10B is cheaper at $0.00 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Qwen3.5 122B-A10B has lower latency, with a time to first token of 0.51s compared with 1.40s.
Which model has a larger context window?
Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 262.1K tokens.
Veredicto
Choose Qwen3.5 122B-A10B for medio-sized en-premise multimodal implementación y automatizado documento inteligencia, or choose Claude Opus 5.5 for grande-escala software development agentes, empresarial codebases, y de misión crítica científico síntesis.
Preguntas frecuentes
Which is cheaper: Qwen3.5 122B-A10B or Claude Opus 5.5?+
Qwen3.5 122B-A10B costs $0/1M input and $0/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.
Which model has a larger context window: Qwen3.5 122B-A10B or Claude Opus 5.5?+
Qwen3.5 122B-A10B supports 262K tokens whereas Claude Opus 5.5 supports 1M tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.
Fuentes: Alibaba & Anthropic Official Documentation