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Gemini 3.1 Flash vs Qwen3.5 397B A17B

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 Gemini 3.1 Flash and Qwen3.5 397B A17B.

Google

Gemini 3.1 Flash

Gemini 3.1 Flash is Google's high-speed, cost-efficient multimodal model in the 3.1 generation, purpose-built for high-volume content synthesis, classification, and intelligent routing at scale. Featuring a 1-million-token context window, it can process large batches of documents, customer data, or multimedia content in a single inference pass, dramatically reducing pipeline complexity. At just $0.25/MTok for input, it is one of the most affordable routes to Google-caliber multimodal AI, making it an ideal backbone for production pipelines, data enrichment workflows, and high-frequency API integrations.

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Alibaba

Qwen3.5 397B A17B

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...

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Technical Specifications

SpecificationGemini 3.1 FlashQwen3.5 397B A17B
ProviderGoogleAlibaba
Context Window1,000,000 tokens256,000 tokens
Agent Suitability86/100N/A
Time to First Token (TTFT)150 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-202026-02-16

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.1 Flash

$0.25

Qwen3.5 397B A17B

$0.39

Output Price per Million Tokens

Gemini 3.1 Flash

$1.50

Qwen3.5 397B A17B

$2.45

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
8680.0%vsN/A
Gemini 3.1 Flash
Qwen3.5 397B A17B
HumanEvalPython coding & logic synthesis
8850.0%vsN/A
Gemini 3.1 Flash
Qwen3.5 397B A17B
MATHComplex mathematical problem solving
7820.0%vsN/A
Gemini 3.1 Flash
Qwen3.5 397B A17B
GPQAGraduate-level expert reasoning
6050.0%vsN/A
Gemini 3.1 Flash
Qwen3.5 397B A17B
HellaSwagCommonsense reasoning and inference
9520.0%vsN/A
Gemini 3.1 Flash
Qwen3.5 397B A17B
MT-BenchMulti-turn conversation flow quality
900.0%vsN/A
Gemini 3.1 Flash
Qwen3.5 397B A17B

Gemini 3.1 Flash Quirks & Gotchas

  • โ–ธMost cost-effective Google model โ€” ideal for high-volume pipelines
  • โ–ธContext caching available via Vertex AI for repeated document processing

Qwen3.5 397B A17B Quirks & Gotchas

No developer gotchas reported.