GPT-5.6 Sol vs Grok 4.5
GPT-5.6 Sol vs Grok 4.5 (2026): benchmarks, live pricing, hallucination rates and context compared. Sol leads 86-82; Grok is ~5x cheaper on output and, since July 16, fully available in the EU.
This matchup no longer has a regional shortcut. Until mid-July 2026 the honest advice for European teams was 'Sol by default, because Grok 4.5 is not available in the EU' — that is now obsolete. xAI completed the EU AI Act systemic-risk evaluations and cleared the block: Grok 4.5 has been fully available across Europe since 16 July 2026, with API console access from 17 July, and no VPN. Availability is a tie, so the decision falls back to capability and cost. GPT-5.6 Sol is the stronger model on nearly every capability aggregate — it leads 86-82 overall, takes agentic 92.0 vs 83.3, wins Terminal-Bench 2.0 by 8.6 points and ships 1.05M tokens of context against Grok's 500K. Grok 4.5 is not weaker so much as differently optimised: at $2/$6 per 1M tokens against Sol's $5/$30 it is roughly 5x cheaper on output, it finishes coding-agent tasks on about 1.9M tokens versus 6.2M for the GPT-5.x tier, and it hallucinates far less on hard knowledge (53.5% vs 88.8% on AA-Omniscience). Real-world coding is a dead heat at 64.7% vs 64.6% on SWE-bench Pro. So: pick Sol when peak capability, long context or agentic tool use decides the outcome, and pick Grok 4.5 when you are running thousands of unattended tasks where token cost and factual reliability compound. Note that OpenAI's 30 July 2026 price cut does not change this arithmetic — it reduced Luna by 80% and Terra by 20%, while Sol's price held.
Detailed Comparison
A side-by-side analysis of key factors to help you make the right choice.
| Factor | GPT-5.6 SolRecommended | Grok 4.5 | Winner |
|---|---|---|---|
| Peak benchmark capability | Leads the head-to-head 86-82 overall and wins agentic 92.0 vs 83.3, including a 91.9% vs 83.3% swing on Terminal-Bench 2.0. | Competitive but trails on most measured aggregates; wins only where cost or coding is the deciding factor. | |
| Real-world coding (SWE-bench Pro) | 64.6% on SWE-bench Pro and strong on agentic coding benchmarks like Terminal-Bench. | 64.7% on SWE-bench Pro - edges it by 0.1 points and takes BenchLM's coding aggregate 64.7 vs 64.6. | |
| Token price | $5 input / $30 output per 1M tokens — unchanged by OpenAI's July 30, 2026 price cut, which applied to Luna and Terra only. | $2 input / $6 output per 1M tokens — about 2.5x cheaper on input and 5x cheaper on output. | |
| Cost per task & token efficiency | Sits in the ~$5-per-coding-task tier and consumes far more tokens per task. | ~$2.49 per coding-agent task at just 1.9M tokens per task (vs 6.2M for the GPT-5.x tier, 7.2M for Fable 5); ~4.2x fewer tokens than Opus 4.8 on SWE-bench Pro. | |
| Hallucination rate on hard knowledge | 88.8% hallucination rate on the AA-Omniscience benchmark. | 53.5% hallucination rate - substantially more reliable when it hits the edge of what it knows. | |
| Context window | 1.05M tokens. | 500K tokens. | |
| EU availability (GDPR / data residency) | Generally available in the EU at launch. | Blocked in all 27 EU states at its July 8 launch, but xAI completed the EU AI Act systemic-risk evaluations and cleared the block: @grok announced full European availability on July 16, 2026 and the API console reached EU users on July 17. No VPN required. | |
| Reasoning & knowledge depth | AA Intelligence Index 58.9, AA-LCR 73.7%, CritPt 32.3%, GPQA-Diamond 94.1%. | AA Intelligence Index 53.8 (4th overall), AA-LCR 67.7%, CritPt 15.4%, GPQA-Diamond 93.1%. | |
| Total Score | 3/ 8 | 3/ 8 | 2 ties |
Key Statistics
Real data from verified industry sources to support your decision.
@grok / xAI release notes
OpenRouter models API (verified 31 July 2026)
OpenRouter models API (verified 31 July 2026)
BenchLM.ai
BenchLM.ai
BenchLM.ai
Artificial Analysis via The Decoder
BenchLM.ai (Artificial Analysis)
All statistics come from verified third-party sources. Source, year, and direct link are shown on each metric.
When to Choose Each Option
Clear guidance based on your specific situation and needs.
Choose GPT-5.6 Sol when...
- You need the strongest all-round model: Sol leads the head-to-head 86-82 and wins agentic, reasoning, knowledge and math
- Your workload depends on long context — 1.05M tokens versus Grok's 500K is a 2x difference that no prompt engineering recovers
- Terminal-Bench-style agentic tool use is your primary workload, where the 91.9% vs 83.3% gap is the largest single swing in the matchup
- You are already on the OpenAI stack and the switching cost outweighs a per-token saving
Choose Grok 4.5 when...
- Token cost dominates your bill: at $2/$6 versus $5/$30, Grok is ~2.5x cheaper on input and ~5x on output
- You run high-volume unattended coding agents, where ~1.9M tokens and ~$2.49 per task compounds against the GPT-5.x tier's ~6.2M tokens and ~$5.07
- Factual reliability at the edge of the model's knowledge matters — Grok's 53.5% AA-Omniscience hallucination rate versus Sol's 88.8% is the widest gap on the page
- You are doing real-world repository work, where SWE-bench Pro is a 64.7% vs 64.6% dead heat and you may as well take the cheaper model
Our Recommendation
This matchup no longer has a regional shortcut. Until mid-July 2026 the honest advice for European teams was 'Sol by default, because Grok 4.5 is not available in the EU' — that is now obsolete. xAI completed the EU AI Act systemic-risk evaluations and cleared the block: Grok 4.5 has been fully available across Europe since 16 July 2026, with API console access from 17 July, and no VPN. Availability is a tie, so the decision falls back to capability and cost. GPT-5.6 Sol is the stronger model on nearly every capability aggregate — it leads 86-82 overall, takes agentic 92.0 vs 83.3, wins Terminal-Bench 2.0 by 8.6 points and ships 1.05M tokens of context against Grok's 500K. Grok 4.5 is not weaker so much as differently optimised: at $2/$6 per 1M tokens against Sol's $5/$30 it is roughly 5x cheaper on output, it finishes coding-agent tasks on about 1.9M tokens versus 6.2M for the GPT-5.x tier, and it hallucinates far less on hard knowledge (53.5% vs 88.8% on AA-Omniscience). Real-world coding is a dead heat at 64.7% vs 64.6% on SWE-bench Pro. So: pick Sol when peak capability, long context or agentic tool use decides the outcome, and pick Grok 4.5 when you are running thousands of unattended tasks where token cost and factual reliability compound. Note that OpenAI's 30 July 2026 price cut does not change this arithmetic — it reduced Luna by 80% and Terra by 20%, while Sol's price held.
Frequently Asked Questions
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