GPT-5.6 Luna wins on coding (88 vs 78) and writing quality and price ($0.2 vs $0.3/1M input). For most workflows, GPT-5.6 Luna is the stronger default — best budget model from a frontier lab — near-frontier scores at commodity price.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
GPT-5.6 Luna is the safest overall answer here when you want the strongest default instead of the lowest list price.
Mistral: Mistral Nemo is the lower-cost option to start with when you still need useful output at scale.
Gemini 3.5 Flash-Lite is the better pick when response speed matters more than maximum reasoning depth.
GPT-5.6 Luna leads on coding with a score of 88 vs 78 for Gemini 3.5 Flash-Lite.
GPT-5.6 Luna has the larger context window: 1.05M vs 1.048576M for Gemini 3.5 Flash-Lite.
GPT-5.6 Luna is cheaper at $0.2/1M input tokens vs $0.3/1M for Gemini 3.5 Flash-Lite.
Choose GPT-5.6 Luna for coding and writing — cheap high-throughput summarization.
Choose Gemini 3.5 Flash-Lite when high-volume.
Both models serve different primary workflows — consider using each where it has a clear edge.
Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.
OpenAI / Budget / Aug 6, 2026
Best budget model from a frontier lab — near-frontier scores at commodity price.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
Your workload actually uses the long context window — recall drops to 41% past 512K tokens.
The fastest way to see where the recommendation shifts when your priority changes.
Best budget model from a frontier lab — near-frontier scores at commodity price.
Fastest budget multimodal model — 350 tokens/sec at Lite pricing.
Punches far above its price: GPQA Diamond 92.3%, SWE-bench Pro 62.7%, Terminal-Bench 2.1 84.7%
$0.20/$1.20 per 1M after the July 30, 2026 price cut — dramatically cheaper per token than Gemini 3.6 Flash
Full 1.05M-token context at budget pricing — larger than most rival small models
Long-context recall collapses at scale: 41.3% on 512K–1M token tasks vs Terra's 72.5%
Text and image input only — no video, audio, or native PDF ingestion like Gemini 3.6 Flash
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GPT-5.6 Luna wins on more categories — coding, writing, budget. Gemini 3.5 Flash-Lite is the better pick when high-volume. The right choice depends on your specific use case.
GPT-5.6 Luna is cheaper at $0.2/1M input and $1.2/1M output. Gemini 3.5 Flash-Lite costs $0.3/1M input and $2.5/1M output.
GPT-5.6 Luna has the larger context window at 1.05M tokens vs Gemini 3.5 Flash-Lite's 1.048576M. For large document analysis, GPT-5.6 Luna is the stronger pick.
GPT-5.6 Luna is better for coding with a score of 88 vs Gemini 3.5 Flash-Lite's 78 (out of 100). Claude Fable 5 is the overall coding leader in this directory at 100/100.
Gemini 3.5 Flash-Lite is faster with a very fast speed rating (score: 5) vs GPT-5.6 Luna's fast rating (score: 4).