Llama 4 Maverick wins on price ($0.6 vs $2/1M input). Gemini 3.1 Pro wins on coding (80 vs 58) and writing quality and context window (2M vs 256K). For most workflows, Gemini 3.1 Pro is the stronger default — best for research and deep document analysis — 2m context at the best premium price.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
Gemini 3.1 Pro is the safest overall answer here when you want the strongest default instead of the lowest list price.
Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.
Google / Premium / Mar 23, 2026
Best for research and deep document analysis — 2M context at the best premium price.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
Your primary use case is writing quality or agentic coding — Claude wins both.
The fastest way to see where the recommendation shifts when your priority changes.
2M token context window — the largest of any frontier model
Leads ARC-AGI-2 reasoning benchmark at 77.1%
Best price-to-performance among premium models at $2/$12 per 1M tokens
Slower than Flash for everyday lightweight tasks
Claude Sonnet 4.6 is better for writing quality
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Gemini 3.1 Pro wins on more categories — research, long context, reasoning. Llama 4 Maverick is the better pick when flexible self-hosted deployments and mixed general workloads. The right choice depends on your specific use case.
Llama 4 Maverick is cheaper at $0.6/1M input and $1.6/1M output. Gemini 3.1 Pro costs $2/1M input and $12/1M output.
Gemini 3.1 Pro has the larger context window at 2M tokens vs Llama 4 Maverick's 256K. For large document analysis, Gemini 3.1 Pro is the stronger pick.
Gemini 3.1 Pro is better for coding with a score of 80 vs Llama 4 Maverick's 58. For the highest coding quality available, Claude Sonnet 4.6 (79.6% SWE-bench) or Opus 4.6 (80.8%) remain benchmarks.
Llama 4 Maverick is faster with a fast speed rating (score: 4) vs Gemini 3.1 Pro's balanced rating (score: 3).
Google: Gemma 2 9B is the lower-cost option to start with when you still need useful output at scale.
Llama 4 Maverick is the better pick when response speed matters more than maximum reasoning depth.
Gemini 3.1 Pro leads on coding with a score of 80 vs 58 for Llama 4 Maverick.
Gemini 3.1 Pro has the larger context window: 2M vs 256K for Llama 4 Maverick.
Llama 4 Maverick is cheaper at $0.6/1M input tokens vs $2/1M for Gemini 3.1 Pro.
Choose Gemini 3.1 Pro for research and long context — research.
Choose Llama 4 Maverick when flexible self-hosted deployments and mixed general workloads.
Llama 4 Maverick is the more cost-efficient option at $0.6/1M — worth considering if token volume is a concern.
