Best Value LLM in October 2026: AI Capability vs Price

Jonhisking · October 4, 2026

Is the most expensive AI model the smartest one? We put 23 models' capability scores next to their API prices to find out. Short answer: no. The best model costs half of what the second-best costs, and a model at 5% of the top price lands within 13 points of it.

Scores come from the Epoch Capabilities Index (ECI), which combines dozens of benchmarks (math, coding, science, reasoning) into one scale. Prices are standard API list prices, checked October 4, 2026.

Models on the green line are the best-value frontier: no other model is both cheaper and more capable. Anything below the line costs more than a frontier model with the same or higher score.

The short version

A chat request here is 1,500 input and 400 output tokens of English text. Costs include each model's tokenizer difference: Claude counts about 30% more tokens than GPT for the same text, and that is already in the numbers.

1. Top capability: Claude Opus 5.5

Claude Opus 5.5 has the highest score, 167.3. At $4 input and $20 output per million tokens, it is also far from the most expensive model at the top. GPT-6 Astra is close behind at 166.5, but costs $10 / $50, so 10,000 chat requests run $350 against Opus's $182.

The two are within each other's margin of error, so for most work you will not notice a quality gap. You will notice the bill.

2. Best value: Claude Sonnet 5.5

Claude Sonnet 5.5 scores 165.2, just 2.2 points under Opus, for half the price ($2 / $10). That gap is within the margin of error too. If you are choosing one model for a product today, this is the one the chart points to.

3. Cheap and strong: Gemini 3.8 Flash and DeepSeek V4 Flash

• Gemini 3.8 Flash (156.9) costs $0.75 / $3.75. 10,000 chat requests: about $25.
• DeepSeek V4 Flash (154.5) costs $0.30 / $1.20. 10,000 chat requests: about $9, or 5% of Opus.

Both sit about 10 to 13 points below the top. For classification, extraction, summaries and most chatbot traffic, that is often enough, and the savings are 7 to 20 times.

4. Expensive for what you get

These models cost more than a frontier model that scores the same or higher:

That does not make them bad models. They may do better on a specific task than the overall score suggests. But if you use them by default, test the cheaper option on your own prompts first.

5. What about GPT-6 Sol?

GPT-6 Sol is the model most people actually use, so it is the obvious gap in the chart. Epoch AI has not scored it yet, but one independent result is out on a different scale: on the Artificial Analysis Intelligence Index (v4.3.2, max reasoning effort, September 30), GPT-6.1 Sol scores 51.8 against GPT-6 Astra's 52.7.

That is near-Astra capability at a fifth of the price ($2 / $10 against $10 / $50). If that holds when Epoch adds it, Sol would land on the best-value line next to Claude Sonnet 5.5, which has the same list price. The two scores use different scales, so they are not placed on the chart above.

6. Not scored yet

GPT-6 Sol, GPT-6 Luna, GPT-6.1 Sol, Gemini 4 Argon and Grok 4.7 are too new for a capability score. They will join the live ranking automatically once Epoch AI publishes one.

How to use this

1. Start from the frontier: Sonnet 5.5 for quality, Gemini 3.8 Flash or DeepSeek V4 Flash for volume.
2. Test two or three of them on 20 real prompts from your app. The overall score is general capability, not your task.
3. Check what your actual prompts cost on each model with the token counter, including the tokenizer difference.

The chart and table update every day as prices and scores change: see the AI model ranking.

Capability scores: Epoch Capabilities Index by Epoch AI, used under CC BY 4.0. Prices: standard API list prices, no caching or batch discounts, checked October 4, 2026.

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