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Gemini 3.5 Flash vs R1 Distill Llama 70B

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 3.5 Flash and R1 Distill Llama 70B.

Google

Gemini 3.5 Flash

Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution...

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DeepSeek

R1 Distill Llama 70B

DeepSeek R1 Distill Llama 70B is a distilled large language model based on [Llama-3.3-70B-Instruct](/meta-llama/llama-3.3-70b-instruct), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). The model combines advanced distillation techniques to achieve high performance across...

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Technical Specifications

SpecificationGemini 3.5 FlashR1 Distill Llama 70B
ProviderGoogleDeepSeek
Context Window1,048,576 tokens128,000 tokens
Agent Suitability88/100N/A
Time to First Token (TTFT)200 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-05-192025-01-23

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.5 Flash

$1.50

R1 Distill Llama 70B

$0.80

Output Price per Million Tokens

Gemini 3.5 Flash

$9.00

R1 Distill Llama 70B

$0.80

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
9050.0%vs8520.0%
Gemini 3.5 Flash
R1 Distill Llama 70B
HumanEvalPython coding & logic synthesis
9210.0%vs8830.0%
Gemini 3.5 Flash
R1 Distill Llama 70B
MATHComplex mathematical problem solving
8500.0%vs7000.0%
Gemini 3.5 Flash
R1 Distill Llama 70B
GPQAGraduate-level expert reasoning
6820.0%vs4450.0%
Gemini 3.5 Flash
R1 Distill Llama 70B
HellaSwagCommonsense reasoning and inference
9780.0%vs8600.0%
Gemini 3.5 Flash
R1 Distill Llama 70B
MT-BenchMulti-turn conversation flow quality
920.0%vs905.0%
Gemini 3.5 Flash
R1 Distill Llama 70B

Gemini 3.5 Flash Quirks & Gotchas

  • โ–ธExcellent multimodal performance โ€” native video understanding
  • โ–ธTool calling via Google's native function_declarations in Vertex AI

R1 Distill Llama 70B Quirks & Gotchas

No developer gotchas reported.