GPT-6 Sol (max) vs. GPT-5.6 Sol (max)

This analysis compares OpenAI’s GPT-6 Sol (max) and GPT-5.6 Sol (max). While the newer GPT-6 model offers significant speed improvements and lower costs, the GPT-5.6 variant maintains a broader benchmark profile, providing a nuanced trade-off between raw throughput and established performance metrics for specialized tasks.

By the numbers

These figures describe the two model configurations shown here. A dash means the source snapshot had no usable figure for that metric. Scores, speed and API pricing may change as providers update models.

Metric	GPT-6 Sol (max)	GPT-5.6 Sol (max)
Intelligence Index	47.5	47.0
Coding Index	–	77.4
Input price (per 1M tokens)	$2.00	$4.00
Output price (per 1M tokens)	$10.00	$20.00
Output speed (tokens/s)	116	64
Time to first token	97s	83s
Release date	2026-09-22	2026-07-09

What the benchmarks show

Evaluating these two models requires looking beyond simple version numbers, as each excels in different testing environments. GPT-5.6 Sol (max) provides a more comprehensive performance profile, boasting a coding index of 77.4 and strong scores across specialized benchmarks like GPQA (0.941), IFBench (0.726), and TAU2 (0.850). Its performance on the HLE (0.495) and LCR (0.84) benchmarks suggests a high level of reliability for complex, multi-step reasoning tasks.

In contrast, GPT-6 Sol (max) offers a more focused benchmark set. While it trails slightly on the HLE (0.479) and LCR (0.836) metrics compared to its predecessor, it demonstrates competitive results in SciCode (0.576). Because GPT-6 lacks the extensive coding and reasoning indices present in the GPT-5.6 documentation, users should weigh the marginal differences in these shared benchmarks against the specific needs of their application’s logic requirements.

Speed and cost

The most significant differentiator between these two models is their operational efficiency. GPT-6 Sol (max) marks a substantial leap in performance, delivering an output speed of 116.344 tokens per second. This is nearly double the 63.783 tokens per second provided by GPT-5.6 Sol (max). For developers building latency-sensitive applications, this increase in throughput is a critical advantage.

Cost structures further favor the newer model. GPT-6 Sol (max) is priced at a blended rate of $4.00 per million tokens, whereas GPT-5.6 Sol (max) costs $8.00 per million tokens. By effectively halving the cost per token, GPT-6 allows for more extensive usage within the same budget. However, it is worth noting that GPT-6 has a significantly higher time to first token (97.42s) compared to GPT-5.6 (82.549s). This suggests that while GPT-6 is faster once generation begins, it may have a longer initial processing delay, which could impact real-time interactive applications.

Which model fits which workflow

Determining the right fit depends on the nature of the tasks being processed. GPT-6 Sol (max) is optimized for high-volume, cost-sensitive workflows. Its superior output speed makes it ideal for large-scale data processing, content generation at scale, or any application where the total volume of tokens is the primary driver of cost and performance constraints. The lower price point makes it an attractive option for scaling existing operations without increasing infrastructure spend.

GPT-5.6 Sol (max) is better suited for workflows that prioritize precision and proven capability. With its documented coding index and higher performance on specific logic-heavy benchmarks like TerminalBench Hard (0.659), it remains a reliable choice for software development assistance, complex technical documentation, and tasks requiring high-fidelity reasoning. If your current pipeline is already optimized for the specific performance characteristics of the 5.6 architecture, the stability of its benchmark results may outweigh the speed benefits of the newer model.

Frequently asked questions

Is GPT-6 Sol max better than GPT-5.6 Sol max?

It depends on what you need: GPT-6 Sol max scores higher on the intelligence index, 47.5 to 47.0; GPT-6 Sol max is 50% cheaper on blended price; GPT-6 Sol max streams output 1.8 times as fast; and GPT-5.6 Sol max reaches its first token sooner.

Who makes GPT-5.6 Sol max and GPT-6 Sol max?

Both are OpenAI models, listed as separate models in the catalogue. GPT-5.6 Sol max was released on July 9, 2026 and GPT-6 Sol max on September 22, 2026.

How much do GPT-5.6 Sol max and GPT-6 Sol max cost?

GPT-6 Sol max is cheaper on a blended basis. GPT-5.6 Sol max lists $4.00 per million input tokens and $20.00 per million output tokens; GPT-6 Sol max lists $2.00 and $10.00. For 1 million input and 200,000 output tokens that is $8.00 against $4.00.

Which is faster, GPT-5.6 Sol max or GPT-6 Sol max?

GPT-6 Sol max generates output faster, at 116 tokens per second against 64 tokens per second. GPT-5.6 Sol max reaches its first token sooner (83 seconds against 97 seconds). Counting the first-token wait, GPT-5.6 Sol max finishes short replies first and GPT-6 Sol max pulls ahead beyond about 2,100 tokens.

Which is newer, GPT-5.6 Sol max or GPT-6 Sol max?

GPT-6 Sol max is newer. It was released on September 22, 2026, about 2 months after GPT-5.6 Sol max (July 9, 2026).

Final whistle

Choosing between these models depends on your priority: throughput or breadth. GPT-6 Sol (max) is the clear choice for high-volume, cost-sensitive production environments where speed is paramount. Conversely, GPT-5.6 Sol (max) remains a robust tool for complex reasoning tasks where established benchmark reliability and specific coding performance are required. If your workflow demands rapid token generation at half the cost, transition to GPT-6; if your operations rely on the specific capabilities validated in the GPT-5.6 benchmark suite, maintain your current integration.

Where the numbers come from

The scores, speed and prices in this comparison come from independent third-party model evaluations that Franklin AI syncs each day, and the article was written from a snapshot of them. For the latest results, open the GPT-6 Sol (max) and GPT-5.6 Sol (max) pages. The AI Benchmark methodology explains how that data is collected and shown.

GPT-6 Sol (max) vs. GPT-5.6 Sol (max): A Comparative Analysis

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