Model Comparison

GPT-4 Turbo vs GPT-5.6 SolWhich is better in 2026?

GPT-5.6 Sol significantly outperforms across most benchmarks. GPT-5.6 Sol is 1.3x cheaper per token.

Verdict: GPT-4 Turbo vs GPT-5.6 Sol — which is better?

GPT-4 Turbo (by OpenAI) and GPT-5.6 Sol (by OpenAI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

GPT-4 Turbo outperforms in 0 benchmarks, while GPT-5.6 Sol is better at 1 benchmark (GPQA). GPT-5.6 Sol significantly outperforms across most benchmarks.

On price, GPT-5.6 Sol is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GPT-5.6 Sol also accepts a larger context window (1,050,000 input tokens), making it the stronger choice for long documents and large codebases.

Choose GPT-4 Turbo if…

  • you want predictable pricing at $10.00/M input and $30.00/M output

Choose GPT-5.6 Sol if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • cost matters — it's about 1.3x cheaper per token
  • you process long inputs — it offers a 1,050,000 token context window
  • you want the most recent training data — it shipped Jul 2026

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GPT-4 Turbo outperforms in 0 benchmarks, while GPT-5.6 Sol is better at 1 benchmark (GPQA).

GPT-5.6 Sol significantly outperforms across most benchmarks.

Sat Jul 18 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GPT-5.6 Sol costs less

For input processing, GPT-4 Turbo ($10.00/1M tokens) is 2.0x more expensive than GPT-5.6 Sol ($5.00/1M tokens).

For output processing, GPT-4 Turbo ($30.00/1M tokens) costs the same as GPT-5.6 Sol ($30.00/1M tokens).

In conclusion, GPT-4 Turbo is more expensive than GPT-5.6 Sol.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Jul 18 2026 • llm-stats.com
OpenAI
GPT-4 Turbo
Input tokens$10.00
Output tokens$30.00
Best providerAzure
OpenAI
GPT-5.6 Sol
Input tokens$5.00
Output tokens$30.00
Best providerOpenAI
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

GPT-5.6 Sol accepts 1,050,000 input tokens compared to GPT-4 Turbo's 128,000 tokens. GPT-5.6 Sol can generate longer responses up to 128,000 tokens, while GPT-4 Turbo is limited to 4,096 tokens.

OpenAI
GPT-4 Turbo
Input128,000 tokens
Output4,096 tokens
OpenAI
GPT-5.6 Sol
Input1,050,000 tokens
Output128,000 tokens
Sat Jul 18 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-5.6 Sol supports multimodal inputs, whereas GPT-4 Turbo does not.

GPT-5.6 Sol can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-4 Turbo

Text
Images
Audio
Video

GPT-5.6 Sol

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

GPT-4 Turbo

Proprietary

Closed source

GPT-5.6 Sol

Proprietary

Closed source

Release Timeline

When each model was launched

GPT-4 Turbo was released on 2024-04-09, while GPT-5.6 Sol was released on 2026-07-09.

GPT-5.6 Sol is 27 months newer than GPT-4 Turbo.

GPT-4 Turbo

Apr 9, 2024

2.3 years ago

GPT-5.6 Sol

Jul 9, 2026

1 weeks ago

2.2yr newer

Knowledge Cutoff

When training data ends

GPT-4 Turbo has a knowledge cutoff of 2023-12-31, while GPT-5.6 Sol has a cutoff of 2026-02-16.

GPT-5.6 Sol has more recent training data (up to 2026-02-16), making it potentially better informed about events through that date compared to GPT-4 Turbo (2023-12-31).

GPT-4 Turbo

Dec 2023

GPT-5.6 Sol

Feb 2026

2.2 yr newer

Provider Availability

GPT-4 Turbo is available from Azure, OpenAI. GPT-5.6 Sol is available from OpenAI.

GPT-4 Turbo

azure logo
Azure
Input Price:Input: $10.00/1MOutput Price:Output: $30.00/1M
openai logo
OpenAI
Input Price:Input: $10.00/1MOutput Price:Output: $30.00/1M

GPT-5.6 Sol

openai logo
OpenAI
Input Price:Input: $5.00/1MOutput Price:Output: $30.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

No standout differentiators in the data we have for this pair.

Larger context window (1,050,000 tokens)
Supports multimodal inputs
Less expensive input tokens
Higher GPQA score (94.6% vs 48.0%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against GPT-4 Turbo and GPT-5.6 Sol side-by-side, then vote on the output you prefer.

GPT-4 Turbo
✓ Preferred
GPT-5.6 Sol
Open in Playground
AI Model Comparison Table
Feature
OpenAI
GPT-4 Turbo
OpenAI
GPT-5.6 Sol

FAQ

Common questions about GPT-4 Turbo vs GPT-5.6 Sol.

Which is better, GPT-4 Turbo or GPT-5.6 Sol?

GPT-5.6 Sol significantly outperforms across most benchmarks. GPT-4 Turbo is made by OpenAI and GPT-5.6 Sol is made by OpenAI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GPT-4 Turbo compare to GPT-5.6 Sol in benchmarks?

GPT-4 Turbo scores MGSM: 88.5%, HumanEval: 87.1%, MMLU: 86.5%, DROP: 86.0%, MATH: 72.6%. GPT-5.6 Sol scores Connectors: 100.0%, Capture-the-Flag Challenges (Internal): 96.7%, HealthBench Consensus: 95.5%, GPQA: 94.6%, MRCR v2 (8-needle): 91.5%.

Is GPT-4 Turbo cheaper than GPT-5.6 Sol?

GPT-5.6 Sol is 2.0x cheaper for input tokens. GPT-4 Turbo costs $10.00/M input and $30.00/M output via azure. GPT-5.6 Sol costs $5.00/M input and $30.00/M output via openai.

What are the context window sizes for GPT-4 Turbo and GPT-5.6 Sol?

GPT-4 Turbo supports 128K tokens and GPT-5.6 Sol supports 1.1M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-4 Turbo and GPT-5.6 Sol?

Key differences include context window (128K vs 1.1M), input pricing ($10.00 vs $5.00/M), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.