How to use Model Selector for Finance
Input task type, latency budget, cost budget, context size, and quality sensitivity. The page returns ranked model recommendations with rationale grounded in published benchmarks rather than vibes.
What It Does
Use the calculator with intent
Input task type, latency budget, cost budget, context size, and quality sensitivity. The page returns ranked model recommendations with rationale grounded in published benchmarks rather than vibes.
Builders picking a model for a new task who want a defensible recommendation based on benchmark data, not Twitter consensus.
Interpreting Results
Rationale matters more than rank — a model recommended for cost may not fit a quality-sensitive task. Read the rationale column to understand why the rank order is what it is.
Input Steps
Field by field
- 1
Enter inputs
Enter task type, accuracy requirement (acceptable percentage), latency budget (max acceptable response time), and monthly call volume.
- 2
Read outputs
Read the recommended model with the cost and latency it implies.
- 3
Toggle setting
Toggle the cost-vs-latency-vs-accuracy axes to see the Pareto frontier — there are usually 2-3 reasonable choices, not one.
- 4
Step 4
Cross-check the recommendation against the methodology page's per-task accuracy benchmarks.
- 5
Re-run
Re-run when you scale call volume by 5x or more — the cost-optimal model often changes at scale.
Common Scenarios
Use realistic starting points
Cost-sensitive extraction task
Task
structured extraction
Budget
tight
Haiku or Gemini Flash typically lead; rationale explains the benchmark on extraction tasks for the chosen models.
Quality-sensitive research task
Task
analytical research
Quality sensitivity
high
Opus or GPT-5 lead; the cost premium is justified by sustained quality differences in long-form reasoning benchmarks.
Try These Tools
Run the numbers next
Token-Cost Optimizer
Compute the dollar cost of a trading research loop across Claude, GPT, and Gemini. Prompt length × model × retry × call volume → cost per idea and per.
Fallback Chain Simulator
Define a provider fallback chain, simulate rate-limit and latency failures, and see p50/p95/p99 latency, success rate, total cost, and degradation-event.
Earnings-Call Summarization Cost Calculator
LLM cost per stock per quarter to summarize earnings transcripts across Sonnet, Opus, GPT-4o, Gemini 2.5 Pro/Flash. Cache-hit-rate aware. Snapshot pricing.
FAQ
Questions people ask next
The short answers readers usually want after the first pass.
Related Content
Keep the topic connected
Agent-Cost Envelope
The agent-cost envelope: the loop of (calls × tokens × retries × model_price) that determines the dollar cost of an LLM-driven trading agent per decision.
Model Drift
Model drift: when an LLM's behavior changes between calls, versions, or weeks. The monitoring stack that catches it before production breaks.