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Gemini 3.1 Flash vs Llama 3.3 70B Instruct

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 Llama 3.3 70B Instruct.

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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Meta

Llama 3.3 70B Instruct

Meta's state-of-the-art open weights model, providing enterprise-grade reasoning and logic. Exceptionally powerful for self-hosted customer support, text generation, and tooling workflows.

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Technical Specifications

SpecificationGemini 3.1 FlashLlama 3.3 70B Instruct
ProviderGoogleMeta
Context Window1,000,000 tokens131,072 tokens
Agent Suitability86/10083/100
Time to First Token (TTFT)150 ms280 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-202024-12-06

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.1 Flash

$0.25

Llama 3.3 70B Instruct

$0.10

Output Price per Million Tokens

Gemini 3.1 Flash

$1.50

Llama 3.3 70B Instruct

$0.32

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%vs8620.0%
Gemini 3.1 Flash
Llama 3.3 70B Instruct
HumanEvalPython coding & logic synthesis
8850.0%vs8800.0%
Gemini 3.1 Flash
Llama 3.3 70B Instruct
MATHComplex mathematical problem solving
7820.0%vs7500.0%
Gemini 3.1 Flash
Llama 3.3 70B Instruct
GPQAGraduate-level expert reasoning
6050.0%vs5200.0%
Gemini 3.1 Flash
Llama 3.3 70B Instruct
HellaSwagCommonsense reasoning and inference
9520.0%vs8850.0%
Gemini 3.1 Flash
Llama 3.3 70B Instruct
MT-BenchMulti-turn conversation flow quality
900.0%vs880.0%
Gemini 3.1 Flash
Llama 3.3 70B Instruct

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

Llama 3.3 70B Instruct Quirks & Gotchas

  • โ–ธStable, well-documented self-hosted option with strong community support
  • โ–ธOutperformed by Llama 4 Maverick for agentic tool-calling workflows