Head-to-head AI model comparison graphic: Claude Haiku 5.5 (Anthropic) vs GPT-6 Sol (OpenAI). Intelligence index 36.5 vs 44.2; output speed 233 vs 127 tokens per second; time to first token 4.6 min vs 91s; output price $0.50 vs $10.00 per million tokens; input price $0.10 vs $2.00 per million tokens. franklineh.com
Claude Haiku 5.5 vs GPT-6 Sol: head-to-head AI benchmark comparison. Claude Haiku 5.5 leads on output speed, output price and input price; GPT-6 Sol leads on intelligence index and time to first token.
Head to headUpdated

Claude Haiku 5.5 Max vs GPT-6 Sol Max compared

GPT-6 Sol Max leads the intelligence index 44.2 to 36.5. Claude Haiku 5.5 Max costs 95% less on blended price. See token costs, speed and which to pick.

Pick it for Claude Haiku 5.5 · Max

  • Lower cost: $0.20 against $4.00 for 1 million input and 200,000 output tokens.
  • Higher throughput once writing (233 tokens per second against 127 tokens per second), though it only finishes first beyond about 52,000 tokens.

Pick it for GPT-6 Sol · Max

  • Higher intelligence index: 44.2 against 36.5.
  • Shorter wait for the first token: 91 seconds against 4.6 minutes.
  • Finishes a typical reply sooner: about 94 seconds against 4.7 minutes for 400 tokens, counting the first-token wait.

By the numbers

MetricClaude Haiku 5.5 (Max)GPT-6 Sol (Max)
Intelligence Index36.544.2
Input price (per 1M tokens)$0.10$2.00
Output price (per 1M tokens)$0.50$10.00
Output speed (tokens/s)233127
Time to first token4.6 min91s
Release date2026-10-072026-09-22

Claude Haiku 5.5 (Max) from Anthropic and GPT-6 Sol (Max) from OpenAI are both tracked in Franklin AI's benchmark catalogue. Price separates them more than anything else; on a blended basis GPT-6 Sol Max costs 20 times as much as Claude Haiku 5.5 Max. No hands-on testing went into this write-up; it summarises the recorded benchmark, price and speed data for both models.

Price per token

Claude Haiku 5.5 Max lists $0.10 per million input tokens and $0.50 per million output tokens; GPT-6 Sol Max lists $2.00 and $10.00. GPT-6 Sol Max costs 20 times as much per output token.

Take 1 million input tokens and 200,000 output tokens: that comes to $0.20 on Claude Haiku 5.5 Max and $4.00 on GPT-6 Sol Max. Scale it up to classifying 100,000 short messages at 150 input tokens and 5 output tokens each and the bill is $1.75 for Claude Haiku 5.5 Max against $35.00 for GPT-6 Sol Max. On a 3:1 blend of input to output tokens, that works out to $0.20 versus $4.00 per million.

Reasoning and overall scores

On the intelligence index, Claude Haiku 5.5 Max scores 36.5 against 44.2 for GPT-6 Sol Max. A lead of this size is hard to dismiss as noise. Put another way, Claude Haiku 5.5 Max would need 21% more on this index to draw level.

Among 109 active scored models, Claude Haiku 5.5 Max sits 37th and GPT-6 Sol Max 26th.

For coding or maths work specifically, the catalogue has no dedicated index on either side yet.

Speed and latency

Once a response is under way, Claude Haiku 5.5 Max produces roughly 233 tokens per second against 127 tokens per second for GPT-6 Sol Max. Claude Haiku 5.5 Max is ahead by 83% on throughput. Before any text appears, Claude Haiku 5.5 Max takes 4.6 minutes and GPT-6 Sol Max 91 seconds. On total time, GPT-6 Sol Max wins at ordinary lengths; Claude Haiku 5.5 Max's higher throughput only pays off beyond about 52,000 tokens. Waits that long are felt on every chat-style request, though they matter less for batch jobs.

For a 400-token response, first token plus generation comes to roughly 4.7 minutes on Claude Haiku 5.5 Max and 94 seconds on GPT-6 Sol Max.

Cost per point of intelligence

A blunt value measure, blended price over intelligence score, puts Claude Haiku 5.5 Max at $0.0055 and GPT-6 Sol Max at $0.090 per point. GPT-6 Sol Max costs 17 times as much per point, which is the price of its lead.

Which is newer

The release dates are September 22, 2026 for GPT-6 Sol Max and October 7, 2026 for Claude Haiku 5.5 Max, 15 days apart. They are effectively contemporaries.

FAQ

Is GPT-6 Sol Max better than Claude Haiku 5.5 Max?

Neither wins everywhere: GPT-6 Sol Max scores higher on the intelligence index, 44.2 to 36.5; Claude Haiku 5.5 Max is 95% cheaper on blended price; Claude Haiku 5.5 Max streams output 1.8 times as fast; and GPT-6 Sol Max reaches its first token sooner.

Which is faster, Claude Haiku 5.5 Max or GPT-6 Sol Max?

Claude Haiku 5.5 Max generates output faster, at 233 tokens per second against 127 tokens per second. GPT-6 Sol Max reaches its first token sooner (91 seconds against 4.6 minutes). Counting the first-token wait, GPT-6 Sol Max finishes first for any reply shorter than about 52,000 tokens.

Are Claude Haiku 5.5 Max and GPT-6 Sol Max from the same company?

Claude Haiku 5.5 Max is made by Anthropic and GPT-6 Sol Max by OpenAI. Claude Haiku 5.5 Max was released on October 7, 2026 and GPT-6 Sol Max on September 22, 2026.

Which is newer, Claude Haiku 5.5 Max or GPT-6 Sol Max?

Claude Haiku 5.5 Max is newer. It was released on October 7, 2026, 15 days after GPT-6 Sol Max (September 22, 2026).

How much do Claude Haiku 5.5 Max and GPT-6 Sol Max cost?

Claude Haiku 5.5 Max is cheaper on a blended basis. Claude Haiku 5.5 Max lists $0.10 per million input tokens and $0.50 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 $0.20 against $4.00.

Final whistle

The verdict: on balance the numbers favour Claude Haiku 5.5 Max, though GPT-6 Sol Max keeps a case of its own. Pick Claude Haiku 5.5 Max if cost matters ($0.50 against $10.00 per million output tokens) and you generate very long outputs, beyond about 52,000 tokens. Pick GPT-6 Sol Max if you need the higher overall score (44.2 against 36.5) and users are waiting on the first word.

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 Claude Haiku 5.5 (Max) and GPT-6 Sol (Max) pages. The AI Benchmark methodology explains how that data is collected and shown.

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