LLM Reference

GPT-5.5 vs Qwen3.5-122B-A10B

GPT-5.5 (2026) and Qwen3.5-122B-A10B (2026) are frontier-tier reasoning models from OpenAI and Alibaba. GPT-5.5 ships a 1.05m-token context window, while Qwen3.5-122B-A10B ships a 262k-token context window. On MMLU PRO, GPT-5.5 leads by 1.4 pts. On pricing, GPT-5.5 ranges from $5 to $8/1M input tokens by tier; Qwen3.5-122B-A10B costs $0.26/1M input tokens. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

GPT-5.5 fits 4x more tokens; pick it for long-context work and Qwen3.5-122B-A10B for tighter calls.

Decision scorecard

Local evidence first
SignalGPT-5.5Qwen3.5-122B-A10B
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentsreasoning-heavy apps, multimodal apps, and tool-calling agents
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window1.05m262k
Cheapest output$30/1M tokens$2.08/1M tokens
Provider routes4 tracked3 tracked
Shared benchmarksMMLU PRO leader6 shared

Decision tradeoffs

Choose GPT-5.5 when...
  • GPT-5.5 holds a shared-benchmark lead on MMLU PRO, ahead by 1.4 points.
  • GPT-5.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • GPT-5.5 has broader tracked provider coverage for fallback and route flexibility.
  • GPT-5.5 uniquely exposes Code execution in local model data.
  • Local decision data tags GPT-5.5 for Coding, RAG, and Agents.
Choose Qwen3.5-122B-A10B when...
  • Qwen3.5-122B-A10B has the lower cheapest tracked output price at $2.08/1M tokens.
  • Local decision data tags Qwen3.5-122B-A10B for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate Qwen3.5-122B-A10B

GPT-5.5

$11,500

Cheapest tracked route/tier: OpenAI API 0-272K input tokens

Qwen3.5-122B-A10B

$728

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $10,772. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

GPT-5.5 -> Qwen3.5-122B-A10B
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Qwen3.5-122B-A10B is $27.92/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Code execution before moving production traffic.
Qwen3.5-122B-A10B -> GPT-5.5
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • GPT-5.5 is $27.92/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • GPT-5.5 adds Code execution in local capability data.

Specs

Specification
Released2026-04-232026-02-24
Context window1.05m262k
Parameters122B
ArchitectureDecoder OnlyMixture of Experts
LicenseProprietaryApache 2.0OSI-approved
OpennessProprietaryOpen source
WeightsNot releasedAvailable
CodeUnknownUnknown
Commercial useCommercial use: conditionalCommercial use: permitted
Knowledge cutoff2025-12-

Pricing and availability

Pricing attributeGPT-5.5Qwen3.5-122B-A10B
Input price
0-272K input tokens
$5/1M tokens
Standard GPT-5.5 token pricing before the long-context surcharge threshold.
272K+ input tokens
$8/1M tokens
Long-context surcharge applies above 272K input tokens for the full session.
$0.26/1M tokens
Output price
0-272K input tokens
$30/1M tokens
Standard GPT-5.5 token pricing before the long-context surcharge threshold.
272K+ input tokens
$36/1M tokens
Long-context surcharge applies above 272K input tokens for the full session.
$2.08/1M tokens
Providers

Capabilities

CapabilityGPT-5.5Qwen3.5-122B-A10B
VisionYesYes
MultimodalYesYes
ReasoningYesYes
JSON / Tool useYesYes
Structured outputsYesYes
Code executionYesNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkGPT-5.5Qwen3.5-122B-A10B
MMLU PRO88.186.7
SWE-bench Verified82.672.0
Google-Proof Q&A93.685.7
Humanity's Last Exam41.425.3
BrowseComp84.463.8
MMMU Pro88.376.9

Continue comparing

Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.