Gemini 2.5 Flash vs Llama 4
2026 - Pricing, benchmarks, and use case comparison
Quick take
- •Llama 4 is open-weights - free to self-host with no API costs. Gemini 2.5 Flash requires paid API access.
- •Llama 4 has a 10M context window - 10x larger than Gemini 2.5 Flash's 1M. Better for long documents and large codebases.
- •Llama 4 is open-source: fine-tune it, self-host it, or use any inference provider. Gemini 2.5 Flash is closed-source.
Specs comparison
| Gemini 2.5 Flash | Llama 4 | |
|---|---|---|
| Provider | Google DeepMind | Meta |
| Type | Closed source | Open source |
| Context window | 1M | ✓10M |
| Input / 1M tokens | $0.075 | ✓Free (self-host) |
| Output / 1M tokens | $0.30 | Free (self-host) |
| Release date | 2025-05 | 2025-04 |
Benchmarks
| Benchmark | Gemini 2.5 Flash | Llama 4 |
|---|---|---|
| MMLU | ~89% | ~85% |
| HumanEval | ~85% | - |
Scores sourced from official provider release posts.
Strengths
Gemini 2.5 Flash
- ✓Exceptional price-to-performance ratio
- ✓1M context at near-commodity pricing
- ✓Multimodal support at low cost
- ✓Fast inference latency
- ✓Strong summarization and classification
Llama 4
- ✓Fully open weights - no usage restrictions
- ✓10M context in Llama 4 Scout variant
- ✓Native multimodal support
- ✓Strong performance relative to size
- ✓Enormous ecosystem of community tools and fine-tunes
Which should you choose?
Choose Gemini 2.5 Flash if you need...
- →High-volume, long-context tasks
- →Cost-sensitive production workloads
- →Document and media summarization
- →Retrieval-augmented pipelines
Choose Llama 4 if you need...
- →Self-hosted and on-premise deployments
- →Privacy-sensitive workloads
- →Custom fine-tuning
- →Researchers and open-source builders