A price table tells you which model has the cheaper unit rate. Real teams need a different answer: for the same workload, how much does the monthly bill change if we switch models?
This benchmark compares 12 production-style tasks across GPT-5.4, Claude Sonnet 4.6, Gemini 2.5 Flash, DeepSeek V4 Pro and Qwen Plus using input tokens, output tokens, request volume, hidden overhead and batch discounts.
💡 Base reference: For the full 30+ model price table, see the 2026 AI API Pricing Guide.
Benchmark method
The formula is intentionally simple:
monthly cost = request volume × (input tokens × input price + output tokens × output price) × hidden multiplierThe default hidden multiplier is 1.2, covering retries, logs, monitoring and minor context variance. Batch-friendly workloads are shown separately.
Representative models:
| Tier | Model | Input / output |
|---|---|---|
| High capability | GPT-5.4 | $2.50 / $15 |
| High capability | Claude Sonnet 4.6 | $3 / $15 |
| Low-cost Western | Gemini 2.5 Flash | $0.30 / $2.50 |
| Ultra-low-cost | DeepSeek V4 Pro | $0.14 / $0.28 |
| China-region balanced | Qwen Plus | $0.80 / $2.00 |
For the full model table, use the AI API pricing guide. This article focuses on workload results.
12-task overview
| Task | Token shape | Cheapest practical option | Safer option |
|---|---|---|---|
| Short support reply | low input, low output | DeepSeek V4 Pro | Gemini Flash |
| Long support reply | output-heavy | Qwen Plus | Claude Sonnet |
| RAG FAQ | high input, medium output | Gemini Flash | Claude Sonnet + cache |
| Code completion | very high input, low output | Gemini / Codestral | Claude Sonnet |
| Code review | high input, high output | Gemini Flash | GPT-5.4 |
| Content outline | medium input/output | Qwen Plus | Claude Sonnet |
| Long-form writing | output-heavy | Gemini Flash | Claude Sonnet |
| Information extraction | high input, low output | DeepSeek + batch | Gemini Flash |
| Batch classification | low input, tiny output | DeepSeek | Qwen Turbo |
| Agent tool loop | multi-turn, high output | Gemini / Qwen | Claude Sonnet |
| Document summary | very high input, medium output | Gemini Flash | Gemini Pro |
| Structured JSON | controlled output | DeepSeek | GPT-4.1 mini |
Short support reply
Profile: 300 input tokens, 120 output tokens, 1M requests/month.
| Model | Estimated monthly cost |
|---|---|
| GPT-5.4 | $3,060 |
| Claude Sonnet 4.6 | $3,240 |
| Gemini 2.5 Flash | $468 |
| DeepSeek V4 Pro | $91 |
| Qwen Plus | $576 |
Short support does not need top-tier reasoning. If response quality passes your QA threshold, DeepSeek / Gemini / Qwen beat Claude/GPT on cost.
Long support reply
Profile: 500 input tokens, 600 output tokens, 300K requests/month.
| Model | Estimated monthly cost |
|---|---|
| GPT-5.4 | $3,690 |
| Claude Sonnet 4.6 | $3,780 |
| Gemini 2.5 Flash | $594 |
| DeepSeek V4 Pro | $111 |
| Qwen Plus | $576 |
Output tokens dominate. Before switching providers, compress output length. The practical tactics are covered in AI output token compression methods.
RAG FAQ
Profile: 6000 input tokens retrieved per query, 500 output tokens, 200K requests/month.
| Model | Estimated monthly cost |
|---|---|
| GPT-5.4 | $5,400 |
| Claude Sonnet 4.6 | $5,940 |
| Gemini 2.5 Flash | $1,008 |
| DeepSeek V4 Pro | $269 |
| Qwen Plus | $1,344 |
RAG is input-cost driven. With 60% cache hit, Claude Sonnet drops to roughly $3,000/month, but Gemini Flash still has a major cost advantage. For deeper RAG math, see RAG chatbot cost estimates.
Code completion
Profile: 3000 input tokens, 150 output tokens, 500K requests/month.
| Model | Estimated monthly cost |
|---|---|
| GPT-5.4 | $5,850 |
| Claude Sonnet 4.6 | $7,425 |
| Gemini 2.5 Flash | $765 |
| DeepSeek V4 Pro | $273 |
| Qwen Plus | $1,530 |
Code completion cost is mostly context. Trim the context window before changing models.
Code review
Profile: 8000 input tokens, 1200 output tokens, 50K reviews/month.
| Model | Estimated monthly cost |
|---|---|
| GPT-5.4 | $2,280 |
| Claude Sonnet 4.6 | $2,520 |
| Gemini 2.5 Flash | $300 |
| DeepSeek V4 Pro | $86 |
| Qwen Plus | $480 |
Use a two-layer review path: cheaper models for formatting and simple patterns, Claude/GPT only for high-risk diffs.
Content outline
Profile: 1500 input tokens, 800 output tokens, 100K requests/month.
| Model | Estimated monthly cost |
|---|---|
| GPT-5.4 | $1,890 |
| Claude Sonnet 4.6 | $1,980 |
| Gemini 2.5 Flash | $306 |
| DeepSeek V4 Pro | $60 |
| Qwen Plus | $336 |
Outlines are forgiving. Use mid/low-cost models first and reserve stronger models for final judgment.
Long-form writing
Profile: 2000 input tokens, 2500 output tokens, 20K requests/month.
| Model | Estimated monthly cost |
|---|---|
| GPT-5.4 | $1,020 |
| Claude Sonnet 4.6 | $1,080 |
| Gemini 2.5 Flash | $174 |
| DeepSeek V4 Pro | $29 |
| Qwen Plus | $144 |
Output price matters more than input price. Do not choose a model for writing by input cost alone.
Information extraction
Profile: 4000 input tokens, 200 output tokens, 1M requests/month.
| Model | Standard monthly cost | Batch monthly cost |
|---|---|---|
| GPT-5.4 | $15,600 | $7,800 |
| Claude Sonnet 4.6 | $18,000 | $9,000 |
| Gemini 2.5 Flash | $2,040 | — |
| DeepSeek V4 Pro | $739 | — |
| Qwen Plus | $4,320 | — |
Extraction is perfect for cheap models and strict JSON schemas. The expensive model rarely pays for itself unless the domain is legally or financially risky.
Batch classification
Profile: 800 input tokens, 30 output tokens, 5M requests/month.
| Model | Estimated monthly cost |
|---|---|
| GPT-5.4 | $13,470 |
| Claude Sonnet 4.6 | $15,120 |
| Gemini 2.5 Flash | $1,710 |
| DeepSeek V4 Pro | $744 |
| Qwen Plus | $4,200 |
Classification should be filtered before the model sees it. Rules + embeddings + model for ambiguous rows can cut cost again by 50%.
Agent tool loop
Profile: 6 LLM turns per task, each turn 4000 input + 700 output tokens, 100K tasks/month.
| Model | Estimated monthly cost |
|---|---|
| GPT-5.4 | $8,280 |
| Claude Sonnet 4.6 | $9,720 |
| Gemini 2.5 Flash | $1,260 |
| DeepSeek V4 Pro | $353 |
| Qwen Plus | $2,160 |
Agent cost is loop cost. Limit turns, retries and output length before worrying about one-cent model differences.
Document summary
Profile: 20K input tokens, 1000 output tokens, 20K requests/month.
| Model | Estimated monthly cost |
|---|---|
| GPT-5.4 | $1,560 |
| Claude Sonnet 4.6 | $1,800 |
| Gemini 2.5 Flash | $192 |
| DeepSeek V4 Pro | $73 |
| Qwen Plus | $408 |
For document summaries, split first, summarize sections cheaply, then use a stronger model only for the final synthesis.
Structured JSON output
Profile: 1200 input tokens, 300 output tokens, 1M requests/month.
| Model | Estimated monthly cost |
|---|---|
| GPT-5.4 | $9,000 |
| Claude Sonnet 4.6 | $9,900 |
| Gemini 2.5 Flash | $1,260 |
| DeepSeek V4 Pro | $286 |
| Qwen Plus | $1,440 |
Short field names, enums and JSON schema reduce output tokens directly.
Decision rules
| Goal | Strategy |
|---|---|
| Lowest cost | DeepSeek / small model first; strong model only for failures |
| Stable production | Gemini Flash or Qwen Plus for main path; Claude/GPT for risk paths |
| Hard reasoning | GPT-5.4 / Claude Sonnet |
| Long context | Gemini first, plus chunking and summaries |
| Agents | control loop count, output, retries and context |
The best production setup is rarely one model. Route simple 70-90% traffic to cheap models and reserve strong models for high-risk or high-complexity paths.
FAQ
Why is benchmark cost different from pricing table cost?
Pricing tables show unit rates. Benchmarks include task shape: output length, input size, request volume, retries and batch discounts.
Is the cheapest model always the best choice?
No. If the cheap model increases failures, retries or human review, total cost can be higher.
When should I use Claude or GPT?
For high-risk reasoning, complex code review, agent workflows and tool-calling paths where failure is expensive.
Which tasks are best for batch discounts?
Information extraction, classification, outline generation and offline summarization.
What should I optimize first?
Output length and retry rate. Most unexpected bills come from long answers, failed tool loops and uncompressed context.