Gemini 2.5 Pro vs Llama 4 Maverick
Google vs Meta · Prices checked 12 August 2026
Llama 4 Maverick is the cheaper of the two by a wide margin: $0.320 per million tokens blended against $3.88, roughly 12.1× less. A single 100K-input, 10K-output job costs $0.026 on Llama 4 Maverick against $0.225 on Gemini 2.5 Pro.
Gemini 2.5 Pro leads on 6 of the 6 benchmarks both models report. The widest gap is on LMArena Elo, where Gemini 2.5 Pro leads by 79 points. Gemini 2.5 Pro takes a 1,000,000-token context window against 128,000, giving 7.8× more room for long documents or whole-codebase work.
Pricing and capacity
| Metric | Gemini 2.5 Pro | Llama 4 Maverick | Difference |
|---|---|---|---|
| Input / 1M tokens | $1.25 | $0.200 | 6.3× |
| Output / 1M tokens | $10.00 | $0.600 | 16.7× |
| Blended · 70/30calculated | $3.88 | $0.320 | 12.1× |
| Blended · 50/50calculated | $5.63 | $0.400 | 14.1× |
| Blended · 80/20calculated | $3.00 | $0.280 | 10.7× |
| Blended · 20/80calculated | $8.25 | $0.520 | 15.9× |
| Job cost · 100K + 10Kcalculated | $0.225 | $0.026 | 8.7× |
| Job cost · 1M + 100Kcalculated | $2.25 | $0.260 | 8.7× |
| Context window | 1,000,000 | 128,000 | 7.8× |
Input and output rates are as published by each provider. Blended and job-cost rows are calculated comparison metrics, not published prices — how they are derived.
Benchmarks
| Benchmark | Gemini 2.5 Pro | Llama 4 Maverick | Leader |
|---|---|---|---|
| MMLU | 89% | 85% | Gemini 2.5 Pro |
| GPQA Diamond | 84% | 67% | Gemini 2.5 Pro |
| MATH | 93% | 84% | Gemini 2.5 Pro |
| HumanEval | 92% | 88% | Gemini 2.5 Pro |
| SWE-bench Verified | 64% | 36% | Gemini 2.5 Pro |
| LMArena Elo | 1389 Elo | 1310 Elo | Gemini 2.5 Pro |
Only suites both models report are listed, so a missing score is never shown as a loss. Figures are provider-published or from public leaderboards and are not independently re-run.
What each model is for
Gemini 2.5 Pro
Google · Frontier
Google's flagship Gemini. 1M-token context, native multimodal across text, image, audio and video, with thinking enabled.
- 1M context (2M in private beta)
- Native video + audio understanding
- Strong reasoning with thinking
- Tight Google ecosystem
Llama 4 Maverick
Meta · Frontier
The flagship Llama 4, an MoE-architecture model designed for cheap, high-throughput inference across the open-weights ecosystem.
- MoE for cheap inference
- Open weights
- Wide hosted availability
- Multimodal
Frequently asked questions
Which is cheaper, Gemini 2.5 Pro or Llama 4 Maverick?
Llama 4 Maverick is the cheaper of the two by a wide margin: $0.320 per million tokens blended against $3.88, roughly 12.1× less. A single 100K-input, 10K-output job costs $0.026 on Llama 4 Maverick against $0.225 on Gemini 2.5 Pro. Blended cost weights input at 70% and output at 30%; price your own token split for an exact answer, since the cheaper model on a blended basis is not always cheaper for your workload.
Which performs better, Gemini 2.5 Pro or Llama 4 Maverick?
Gemini 2.5 Pro leads on 6 of the 6 benchmarks both models report. The widest gap is on LMArena Elo, where Gemini 2.5 Pro leads by 79 points. These are the figures each provider or public leaderboard publishes, not results we re-run, and a benchmark average can hide the specific behaviour your workload depends on.
Which has the larger context window, Gemini 2.5 Pro or Llama 4 Maverick?
Gemini 2.5 Pro takes a 1,000,000-token context window against 128,000, giving 7.8× more room for long documents or whole-codebase work. The context window caps everything in a single request: prompt, retrieved documents, conversation history and the model’s own output all share it.
Can I compare Gemini 2.5 Pro and Llama 4 Maverick on my own numbers?
Yes. Open both in the side-by-side comparison tool to see every field at once, or use the token calculator to price your actual prompt and monthly request volume against each model. Both are free and need no sign-up.
Price it for your own workload
Related matchups
Terms used on this page
Prices and scores are recomputed on every deploy from the catalogue. Prices checked 12 August 2026.