GPT-5.5 wins on coding (96 vs 58) and writing quality and context window (1M vs 256K). Llama 4 Maverick wins on price ($0.6 vs $5/1M input). For most workflows, GPT-5.5 is the stronger default — best openai flagship for agentic coding, research, and computer-use work.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
GPT-5.5 is the safest overall answer here when you want the strongest default instead of the lowest list price.
Meta: Llama 3.1 8B Instruct 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.
GPT-5.5 leads on coding with a score of 96 vs 58 for Llama 4 Maverick.
GPT-5.5 has the larger context window: 1M vs 256K for Llama 4 Maverick.
Llama 4 Maverick is cheaper at $0.6/1M input tokens vs $5/1M for GPT-5.5.
Choose GPT-5.5 for coding and research — agentic coding.
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.
Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.
OpenAI / Premium / May 28, 2026
Best OpenAI flagship for agentic coding, research, and computer-use work.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You only care about the highest public coding benchmark score or need a cheaper high-volume model.
The fastest way to see where the recommendation shifts when your priority changes.
Best OpenAI flagship for agentic coding, research, and computer-use work.
Best flexible option for teams that need open-weight portability.
58.6% on SWE-Bench Pro, ahead of GPT-5.4 on the same public coding benchmark
82.7% on Terminal-Bench 2.0 for complex command-line workflows
1M token API context window for large-codebase and document-heavy workflows
Claude Opus 4.7 leads GPT-5.5 on SWE-Bench Pro for pure coding ceiling
Premium API pricing makes it less attractive for high-volume low-risk work
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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GPT-5.5 wins on more categories — coding, research, 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. GPT-5.5 costs $5/1M input and $30/1M output.
GPT-5.5 has the larger context window at 1M tokens vs Llama 4 Maverick's 256K. For large document analysis, GPT-5.5 is the stronger pick.
GPT-5.5 is better for coding with a score of 96 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 GPT-5.5's balanced rating (score: 3).
