Find the right AI model
for what you're building
Answer 3 questions. Get a personalised recommendation across GPT-4o, Claude, Gemini, Llama, Mistral, and DeepSeek — with real API cost estimates for your exact use case. Free. No signup.
Find My Model →Covers GPT-4o · Claude · Gemini · Llama · Mistral · DeepSeek
Used by developers and founders to choose the best LLM for customer support bots, RAG pipelines, coding assistants, document summarisation, content writing, and local deployment. Updated April 2026.
Find your model
Three questions. One clear recommendation.
Estimate your monthly API cost
Pick a use case preset or enter your own token counts.
| Model | Monthly cost | Annual cost |
|---|
Prices approximate. Verify with provider before production.
Built for specific jobs
Every use case has different demands. Pick the right model from the start.
Customer Support
The best LLMs for customer support balance speed, cost, and instruction-following at scale. Claude Haiku 4.5 and Gemini 2.0 Flash lead for high-volume deployments.
See recommendations →Coding Assistant
Models with strong HumanEval and SWE-bench scores dominate here. Claude Sonnet 4.6 and GPT-4o are the top choices for production coding workflows.
See recommendations →Document Summarisation
Long context windows and faithful summarisation matter most. Gemini 2.5 Pro and Claude Sonnet 4.6 handle 100K+ token documents reliably.
See recommendations →RAG Pipelines
Speed and instruction-following outweigh raw benchmark scores for retrieval-augmented generation. Gemini 2.0 Flash and Claude Haiku 4.5 are the top picks.
See recommendations →Content Writing
Creative and editorial tasks reward nuanced instruction following. Claude Sonnet 4.6 and GPT-4o consistently produce the strongest long-form output.
See recommendations →Local Deployment
When data cannot leave your infrastructure, open-weight models running on your own hardware are the only option. Llama 3.3 70B leads the open-source field.
See recommendations →Deep-dive guides
Detailed model recommendations for specific use cases — with benchmark data, cost breakdowns, and honest trade-offs.
Best LLM for Customer Support
Claude Haiku 4.5 vs Gemini 2.0 Flash vs GPT-4o mini — ranked for cost and speed.
Best LLM for RAG
Why speed and instruction-following matter more than benchmark scores for retrieval pipelines.
Best LLM for Document Summarisation
Long context window comparison — which models handle 50K+ token documents without hallucinating.
Best LLM for Local Deployment
Top open-weight models you can run on your own hardware — ranked by capability per parameter.
Best LLM for Content Writing
Claude vs GPT-4o for long-form editorial work — tone, consistency, and instruction following compared.
Best LLM for Data Extraction
Structured output reliability compared across GPT-4o, Claude, and Gemini for production pipelines.
Best LLM for Coding
HumanEval and SWE-bench compared — Claude Sonnet 4.6 vs DeepSeek V3 vs GPT-4o at scale.
Best LLM for Building a Chatbot
Multi-turn coherence, persona consistency, and cost at 5,000 conversations/day — full breakdown.
Best LLM for Small Business
No-code vs API paths, recommended models, and realistic monthly cost estimates for SMB workflows.
Best LLM for Agentic AI
Tool use, multi-step planning, and error recovery — which model runs the most reliable autonomous agents.
Best LLM for Legal Work
Contract review, case research, and document analysis — ranked by hallucination rate and confidentiality options.
Best LLM for Finance
Financial data extraction, earnings analysis, and SEC filing processing — structured output and long-context compared.
Best LLM for Startups
API choice by startup stage — cost modelling from prototype to scale, plus vendor lock-in risk mitigation.
Model comparisons
Head-to-head breakdowns of the leading frontier models.
Claude vs GPT-4o
Writing, coding, tool use, and cost — an honest comparison for developers with no bias.
DeepSeek vs Claude
DeepSeek V3 delivers ~90% of Claude's quality at 9% of the cost — is it worth switching?
Gemini vs GPT-4o
1M vs 128K context window, half the input cost — when Gemini 2.5 Pro wins and when it doesn't.
Cheapest LLM API
Full cost ranking for 8 models — monthly estimates at 1K and 10K requests/day, plus quality break-even analysis.
GPT-4o Alternatives
The best replacements for GPT-4o in 2026 — by quality, cost, context window, and self-hosting option.
LLM specs that matter in production
Context window, input cost, response latency, and structured output support — at a glance.
| Model | Context window | Input cost / 1M tokens | Latency tier | JSON / structured output | Tool use / function calling |
|---|---|---|---|---|---|
| Gemini 2.5 Pro | 1,000,000 tokens | $1.25 | Mid | Native | Yes |
| Gemini 2.0 Flash | 1,000,000 tokens | $0.10 | Fast | Native | Partial |
| Claude Sonnet 4.6 | 200,000 tokens | $3.00 | Mid | Tool use | Yes |
| Claude Haiku 4.5 | 200,000 tokens | $0.80 | Fast | Tool use | Partial |
| GPT-4o | 128,000 tokens | $2.50 | Mid | Native | Yes |
| GPT-4o mini | 128,000 tokens | $0.15 | Fast | Native | Partial |
| DeepSeek V3 | 128,000 tokens | $0.27 | Mid | Partial | Partial |
| Llama 3.3 70B | 128,000 tokens | Self-hosted | Mid | Partial | Partial |
| Mistral Small | 128,000 tokens | $0.10 | Fast | Native | Limited |
Latency tiers: Fast = sub-400ms TTFT typical · Mid = 400ms–900ms · Slow = >900ms. Structured output "Native" = dedicated JSON mode; "Tool use" = schema-enforced via tool/function call API. Last verified: April 2026.
How to cut your LLM API bill
Four techniques developers use in production to reduce OpenAI, Anthropic, and Google API spend — without touching model quality.
Claude and GPT-4o charge near-zero for repeated context hits. Cache static system prompts, knowledge bases, and conversation history prefixes. Most production apps recover costs within hours of enabling it.
Non-urgent jobs — nightly summaries, bulk data extraction, classification queues — qualify for a 50% discount via OpenAI and Anthropic batch endpoints. Results are returned within 24 hours.
Route simple queries (FAQ lookups, intent classification, short replies) to Gemini 2.0 Flash or Claude Haiku. Reserve GPT-4o or Claude Sonnet only for tasks that need frontier reasoning.
Most apps send 3–5× more context per call than necessary. Trim stale conversation turns, compress retrieved chunks, and summarise long histories before each call. Every token trimmed is money saved.
Best LLM for agentic workflows
Function calling, multi-step tool use, and autonomous task completion rank models differently than general benchmarks. Here is what leads in 2026.
- Top-ranked on SWE-bench for autonomous code tasks
- Reliable multi-step reasoning with minimal backtracking
- Handles tool call sequences of 10+ steps without drift
- Strong error recovery when a tool returns unexpected output
- Parallel function invocation in a single inference pass
- Consistent structured JSON outputs across tool schemas
- Broad ecosystem of pre-built integrations and plugins
- Reliable for code interpreter and web browsing agents
- 1M token context — entire codebases or document sets in one call
- Native Google Search grounding for real-time web-aware agents
- Built-in code execution sandbox, no external tool needed
- Cost advantage over GPT-4o at high context lengths
Tools the community relies on
Consistently recommended across r/LocalLLaMA, r/MachineLearning, and developer forums for building and running LLM applications in production.
Unified API that routes across 200+ LLMs from one endpoint. Compare live pricing, auto-fallback between providers on downtime, and switch models without code changes. The r/LocalLLaMA default for multi-model setups.
openrouter.ai →Drop-in OpenAI-compatible proxy that routes to Anthropic, Google, Cohere, Azure, and 100+ providers without changing your SDK calls. Handles logging, per-key spend tracking, and rate limit management out of the box.
litellm.ai →Run your prompts through a test suite like unit tests. Catch quality regressions, red-team for safety issues, and compare outputs across models in CI. Widely used for production LLM quality assurance in developer teams.
promptfoo.dev →Open-source tracing and analytics for LLM applications. Track costs, latency, and output quality per prompt version, user session, or model. The community's preferred open-source alternative to LangSmith.
langfuse.com →Run Llama 3.3, Mistral, DeepSeek, Qwen, and other open-weight models via API — no GPU setup required. Competitive per-token pricing and OpenAI-compatible endpoints. The go-to on r/LocalLLaMA for open-source model access without self-hosting.
together.ai →