The 10 Best Large Language Models

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Lisa Ernst · 17.09.2025 · Technology · 7 min

I wanted to know which LLMs currently deliver the most performance per euro — not just by feel, but with evidence. The decisive factors are verifiable prices per million tokens and solid, publicly auditable quality indicators such as crowd rankings or benchmark bundles ( OpenAI Pricing, Google Gemini Pricing, Anthropic Claude Pricing, LMArena Leaderboard, ArtificialAnalysis Leaderboard). In this explainer you will find a clear classification; the sources are listed directly behind each.

Introduction: What is the price-performance ratio in LLMs?

Price-performance ratio here means: what does a typical text interaction cost in terms of input and output tokens — and what quality do you receive for it (e.g., in chatbot contexts or aggregated benchmarks). The major providers bill per tokens; for OpenAI, Google, and Anthropic pricing is per 1 million (MTok) input and output tokens (OpenAI Pricing, Google Gemini Pricing, Anthropic Claude Pricing). A practical rule of thumb: if a chat on average consumes 1:1 input/output, add both sides to estimate the cost per “prompt pair” (Source: provider price tables, e.g., Google Gemini 2.5 Flash-Lite 0.10 USD/MTok Input, 0.40 USD/MTok Output; together ~0.50 USD per 1M/1M Pair, Google Gemini Pricing).

Current market overview and price developments

Since the start of the year, providers have moved their model rosters and pricing substantially. OpenAI released new price points with GPT-5 (1.25 USD/MTok Input, 10 USD/MTok Output) as well as GPT-5 mini (0.25/2.00) and GPT-5 nano (0.05/0.40) (OpenAI Pricing). Google brings Gemini 2.5 Flash-Lite into stable operation and positions it aggressively at 0.10/0.40 (Batch: 0.05/0.20) and 1M context length (Google Gemini Pricing, Google Developers Blog, Google Cloud Vertex AI). Anthropic releases Sonnet 4 (3/15) and enables 1M-context in beta at premium rates (6/22.5 for >200k input) (Anthropic Claude Pricing). DeepSeek updates V3.1 and lists prices of 0.56 USD/MTok Input (Cache-Miss), 0.07 (Cache-Hit) and 1.68 Output; also announced off-peak discounts which were later withdrawn (DeepSeek Pricing, Reuters DeepSeek, DeepSeek News). In public rankings the top models remain tightly clustered; chatbot arenas and AAII show the quality spectrum transparently (LMArena Leaderboard, ArtificialAnalysis Leaderboard).

A visual representation of the Top 10 Large Language Models highlighting the global significance of these technologies.

Quelle: intelliarts.com

A visual representation of the Top 10 Large Language Models highlighting the global significance of these technologies.

A short clip that makes Gemini 2.5 Flash-Lite’s positioning as a fast, cost-efficient option tangible.

Fact-check: Verified prices and quality indicators

Verified: Concrete price points per MTok are visible on official pages, e.g., GPT-5 mini 0.25/2.00 (OpenAI Pricing), Gemini 2.5 Flash-Lite 0.10/0.40 (Google Gemini Pricing), Claude Haiku 3.5 0.80/1.00 and Sonnet 4 3/15 (Anthropic Claude Pricing), DeepSeek V3.1 0.56 Input (Cache-Miss), 0.07 (Cache-Hit), 1.68 Output (DeepSeek Pricing). The separate price for search-grounding with Gemini (35 USD/1,000 Requests after free tier) (Google Gemini Pricing) and Sonnet language-context surcharges (Anthropic Claude Pricing) are also documented.

Unclear: Exact “quality gaps” between closely competing top models vary by task; crowd rankings (Arena) and aggregators (AAII) are valuable, but not always synonymous with your use-case (LMArena Leaderboard, ArtificialAnalysis Leaderboard).

False/Misleading: “Open-source models are free in production” – inference costs for hosting/third-party providers do apply (example: Llama/Qwen prices per MTok at Together) (Together AI Pricing).

An overview of the best large language models relevant to the price-performance context.

Quelle: teaminindia.co.uk

An overview of the best large language models relevant to the price-performance context.

Practical implications and recommendations

While many developers praise DeepSeek and Qwen due to price pressure, others report sober experiences with Llama releases despite affordable provider tariffs (summary and perspectives) (Business Insider Llama). Proponents of premium reasoning counter that complex tasks justify higher tiers with Sonnet or GPT-5 (Anthropic Claude Pricing, OpenAI Pricing). Public leaderboards show that performance is not monopolized – several models share the top spot depending on task (LMArena Leaderboard).

In practice: choose a default model with excellent price-performance for 80–90% of the load and route only challenging cases to a premium reasoner. Check prices and tools (Search, Caching, Batch) in the official price guides (Google Gemini Pricing, OpenAI Pricing, Anthropic Claude Pricing). Use neutral comparisons for pre-selection (LMArena Leaderboard, ArtificialAnalysis Leaderboard) and evaluate with your own gold prompts. If you want Open-Source, consider fair pricing with Together – e.g., Llama and Qwen variants including the DeepSeek family (Together AI Pricing).

Quelle: YouTube

A short clip illustrating Gemini 2.5 Flash-Lite’s positioning as a fast, cost-efficient option.

Top 10 LLMs by Price-Performance (as of 18.09.2025)

Here is a concise summary of the Top 10 LLMs based on a practical balance of price and performance:

  1. Gemini 2.5 Flash-Lite: 0.10/0.40 MTok; Batch 0.05/0.20; 1M context; ideal for mass deployments (Google Gemini Pricing, Google Developers Blog, Google Cloud Vertex AI).
  2. DeepSeek V3.1 (Non-Thinking): 0.56 Input (Cache-Miss), 0.07 (Cache-Hit), 1.68 Output; strong for coding/reasoning; occasional off-peak discounts announced (DeepSeek Pricing, Reuters DeepSeek).
  3. OpenAI GPT-5 mini: 0.25/2.00 MTok; very balanced ecosystem (OpenAI Pricing).
  4. OpenAI GPT-5 nano: 0.05/0.40 MTok; extremely affordable for classification/summarization (OpenAI Pricing).
  5. Gemini 2.5 Flash: 0.30/2.50 MTok; Batch 0.15/1.25; 1M context; Hybrid-reasoning (Google Gemini Pricing, Google Cloud Vertex AI).
  6. Qwen3 235B (Together AI, FP8 Throughput): 0.20/0.60 MTok; strong at high volumes (Together AI Pricing, LMArena Leaderboard).
  7. Llama 4 Maverick (Together AI): 0.27/0.85 MTok; solid all-around option in an open ecosystem (Together AI Pricing).
  8. Llama 3.1 8B (Together AI): 0.18/0.18 MTok; minimalist and predictably affordable (Together AI Pricing).
  9. Claude Haiku 3.5: 0.80/1.00 MTok; robust and fast for simple to moderate tasks (Anthropic Claude Pricing).
  10. Claude Sonnet 4: 3/15 MTok; 1M-context available (Premium); worth it for tricky reasoning cases despite price (Anthropic Claude Pricing, LMArena Leaderboard).
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