GPT-5.6 Luna wins on coding (88 vs 87) and writing quality. DeepSeek V4-Flash wins on price ($0.14 vs $0.2/1M 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.
DeepSeek V4-Flash 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 87 for DeepSeek V4-Flash.
GPT-5.6 Luna has the larger context window: 1.05M vs 1M for DeepSeek V4-Flash.
DeepSeek V4-Flash is cheaper at $0.14/1M input tokens vs $0.2/1M for GPT-5.6 Luna.
Choose GPT-5.6 Luna for coding and writing — cheap high-throughput summarization.
Choose DeepSeek V4-Flash when high-volume agentic coding and tool-use pipelines.
DeepSeek V4-Flash is the more cost-efficient option at $0.14/1M — 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 / 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.
Best agentic capability per dollar in the directory.
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. DeepSeek V4-Flash is the better pick when high-volume agentic coding and tool-use pipelines. The right choice depends on your specific use case.
DeepSeek V4-Flash is cheaper at $0.14/1M input and $0.28/1M output. GPT-5.6 Luna costs $0.2/1M input and $1.2/1M output.
GPT-5.6 Luna has the larger context window at 1.05M tokens vs DeepSeek V4-Flash's 1M. 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 DeepSeek V4-Flash's 87 (out of 100). Claude Fable 5 is the overall coding leader in this directory at 100/100.
Both GPT-5.6 Luna and DeepSeek V4-Flash have similar speed profiles — rated fast.