← Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

GPT-5.5 vs Qwen3.5 Plus 2026-04-20

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for GPT-5.5 and Qwen3.5 Plus 2026-04-20.

OpenAI

GPT-5.5

GPT-5.5 is OpenAI’s frontier model designed for complex professional workloads, building on GPT-5.4 with stronger reasoning, higher reliability, and improved token efficiency on hard tasks. It features a 1M+ token...

View Full Specs
Alibaba

Qwen3.5 Plus 2026-04-20

Qwen3.5 Plus (April 2026) is a large-scale multimodal language model from Alibaba. It accepts text, image, and video input and produces text output, with a 1M token context window. This...

View Full Specs

Technical Specifications

SpecificationGPT-5.5Qwen3.5 Plus 2026-04-20
ProviderOpenAIAlibaba
Context Window1,050,000 tokens1,000,000 tokens
Agent Suitability95/100N/A
Time to First Token (TTFT)380 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablebeta
API AvailableYesYes
Released Date2026-04-242026-04-27

API Pricing Comparison

Input Price per Million Tokens

GPT-5.5

$5.00

Qwen3.5 Plus 2026-04-20

$0.30

Output Price per Million Tokens

GPT-5.5

$30.00

Qwen3.5 Plus 2026-04-20

$1.80

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
9420.0%vsN/A
GPT-5.5
Qwen3.5 Plus 2026-04-20
HumanEvalPython coding & logic synthesis
9680.0%vsN/A
GPT-5.5
Qwen3.5 Plus 2026-04-20
MATHComplex mathematical problem solving
9350.0%vsN/A
GPT-5.5
Qwen3.5 Plus 2026-04-20
GPQAGraduate-level expert reasoning
8420.0%vsN/A
GPT-5.5
Qwen3.5 Plus 2026-04-20
HellaSwagCommonsense reasoning and inference
9900.0%vsN/A
GPT-5.5
Qwen3.5 Plus 2026-04-20
MT-BenchMulti-turn conversation flow quality
970.0%vsN/A
GPT-5.5
Qwen3.5 Plus 2026-04-20

GPT-5.5 Quirks & Gotchas

  • Best for JSON schema adherence — strict mode available via response_format parameter
  • Requires explicit tool_choice for deterministic function calling

Qwen3.5 Plus 2026-04-20 Quirks & Gotchas

No developer gotchas reported.