Best Value AI Models
DeepSeek V4.1 Flash tops the Value LLMs chart with $0.30 per 1M in. GPT-4o-mini is second with $0.15 per 1M in.
Frontier models are not always the smartest buy. This chart ranks the ten best-value large language models by cost-performance — capability delivered per dollar of inference. A small open-weights model that is 90% as good for 10% of the price outranks a frontier model on value. Prices shown are indicative input rates per 1M tokens and shift often; treat them as a snapshot.
DeepSeek V4.1 Flash
Input $0.30 / output $1.20 per 1M tokens (indicative, peak cache-miss). Open-weights flagship; near-frontier quality at a fraction of the price.
GPT-4o-mini
Input $0.15 / output $0.60 per 1M tokens (indicative). Cheap, fast, multimodal workhorse for production.
Gemini 2.5 Flash
Input $0.30 / output $2.50 per 1M tokens (indicative). High-throughput multimodal model with a generous free tier.
Qwen3-235B
Input $0.20 / output $0.40 per 1M tokens (indicative). Open-weights MoE with strong multilingual coverage.
Llama 4 Maverick
Input $0.20 / output $0.40 per 1M tokens (indicative). Open-weights MoE competing with mid-tier closed models.
Grok 2 mini
Input $0.20 / output $0.40 per 1M tokens (indicative). Fast mini variant with good reasoning per dollar.
GLM-4.5
Input $0.20 / output $0.40 per 1M tokens (indicative). Strong open-weights option with agentic tuning.
Claude Haiku 4.5
Input $1.00 / output $5.00 per 1M tokens (indicative). Cheapest Claude; excellent speed and instruction-following.
Mistral Large
Input $2.00 / output $6.00 per 1M tokens (indicative). European frontier model with solid coding ability.
Phi-4
Input $0.10 / output $0.15 per 1M tokens (indicative). Small-but-mighty model that overperforms its size on reasoning.
Editor’s Notes
- Ranking is editorial by cost-performance (capability per dollar), not a single benchmark score.
- Prices are input rates per 1M tokens, refreshed daily by fetch-ai.js from the litellm price library; falls back to a hardcoded snapshot on failure.
- Prices change frequently — verify before quoting.
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