Gemini 2.5 Flash vs Llama 4 Maverick
Gemini 2.5 Flash vs Llama 4 Maverick: Llama 4 Maverick is cheaper for input-heavy usage ($0.27/M vs $0.30/M input tokens), while Gemini 2.5 Flash is better for long-context tasks (1,000,000 tokens).
Direct answer: choose Llama 4 Maverick for lower token spend and choose Gemini 2.5 Flash when your workload needs longer context.
Compare input and output token pricing, context windows, and monthly cost estimates on one page so you can pick the cheaper model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Gemini 2.5 Flash
Llama 4 Maverick
Cost Differences
Llama 4 Maverick costs less than Gemini 2.5 Flash
Quick Recommendation
Winner for direct API pricing: Llama 4 Maverick. At the default workload, Llama 4 Maverick saves about $2.565/month ($31.2075/year) versus Gemini 2.5 Flash.
Feature Comparison
| Feature | Gemini 2.5 Flash | Llama 4 Maverick |
|---|---|---|
| Provider | Meta (via Together AI) | |
| Input Price | $0.30/1M tokens | $0.27/1M tokens |
| Output Price | $2.50/1M tokens | $0.85/1M tokens |
| Context Window | 1,000,000 tokens | 1,000,000 tokens |
| Max Output | 32,768 tokens | 65,536 tokens |
| Category | efficient | flagship |
| Capabilities | textvisionaudiocode | textvisioncode |
| Release Date | 5/20/2025 | 4/5/2025 |
Gemini 2.5 Flash vs Llama 4 Maverick: Which Should You Choose?
Choosing between Gemini 2.5 Flash and Llama 4 Maverick depends on your priorities: cost efficiency, context length, or raw capability. Llama 4 Maverick is the more affordable option at $0.27/1M input tokens — 10% cheaper than Gemini 2.5 Flash.
These models come from different providers — Google and Meta (via Together AI) — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Google, switching to Meta (via Together AI)involves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Gemini 2.5 Flash is a efficient model while Llama 4 Maverick is flagship. This means they're optimized for different workloads. Llama 4 Maverick targets more demanding workloads, while Gemini 2.5 Flash provides a cost-effective option for everyday tasks.
Output costs matter too. Gemini 2.5 Flash charges $2.50/1M output tokens vs $0.85 for Llama 4 Maverick. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Llama 4 Maverick has the edge here at $0.85/1M output tokens.
Multimodal capabilities: Both models support vision (image understanding), so you can send images alongside text prompts with either option.
Best Use Cases
Choose Gemini 2.5 Flash when:
- • You need more capabilities (audio)
- • You're already using Google's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose Llama 4 Maverick when:
- • Budget is a primary concern
- • You need longer outputs (up to 65,536 tokens)
- • You're already using Meta (via Together AI)'s API ecosystem
Pros and Caveats at a Glance
Gemini 2.5 Flash
- • Input pricing: $0.30/M tokens
- • Output pricing: $2.50/M tokens
- • Context window: 1,000,000 tokens
- • Max output: 32,768 tokens
Watch out for
- • Higher input cost than Llama 4 Maverick
- • Higher output cost than Llama 4 Maverick
Llama 4 Maverick
- • Input pricing: $0.27/M tokens
- • Output pricing: $0.85/M tokens
- • Context window: 1,000,000 tokens
- • Max output: 65,536 tokens
Watch out for
- • Trade-offs are minor in this matchup.
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Gemini 2.5 Flash (Google)
Llama 4 Maverick (Meta (via Together AI))
Start using Gemini 2.5 Flash today
Sign Up for Google →Start using Llama 4 Maverick today
Sign Up for Meta (via Together AI) →Frequently Asked Questions
Which is cheaper, Gemini 2.5 Flash or Llama 4 Maverick?▼
What is the context window difference between Gemini 2.5 Flash and Llama 4 Maverick?▼
Which model is better for AI Chatbot?▼
Which model has better overall pricing for heavy usage?▼
Where can I compare Google and Meta (via Together AI) API pricing beyond this model matchup?▼
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