Undominated.ai

Alternatives to GPT-6.1 Sol

OpenAI LMArena 1445.6 $4.00/M on a balanced workload prices as of 2026-10-06

Every higher-scoring or cheaper alternative has a recorded capability loss.

Of the 144 models carrying both an independent score and a published price at the same delivery mode, 23 score at least as high as GPT-6.1 Sol and cost no more under at least one listed workload, with at least one of those dimensions improved. 22 of them cost less; the rest match the price and have a higher score. 23 have a recorded capability loss, named on every row.

Dominance is not a property of a model. It is a property of a model, a capability lens and a workload, and all three are named on every row. Scores are LMArena Elo, used under CC BY 4.0 from the official dataset; prices are blended per million tokens. A higher score is not a drop-in replacement.

This page is built only while a candidate improves score or price without worsening the other under a listed workload. When that comparison no longer holds, it is not generated.

Where it holds

WorkloadGPT-6.1 Sol $/MRecorded capabilities preservedRecorded capability losses
Balanced$4.00023
Summarise$1.86022
Chat$4.63021
Code gen$6.65021
Agentic$2.07021

Workload mixes are defined on the methodology page. Cached input is priced at the cached rate, and reasoning tokens at the worse of the reasoning and output rates.

What you would be replacing

Intelligence1445.6
Context window1M
Max output128K
Input modesfile, image, text
Tool useyes
Extended reasoningyes

Preserving recorded capabilities requires matching or beating these fields. Full record for GPT-6.1 Sol, or check GPT-6.1 Sol against the whole catalogue.

Alternatives with recorded capability losses 23

These improve score or price without worsening the other under the listed workloads, but reduce at least one recorded capability. Read the last column before switching.

ModelIntelligence$/MHolds underRecorded capability loss
MiMo-V2.6-Pro Xiaomi1491 +45.4$0.540
  • Balanced −87%
  • Summarise −82%
  • Chat −90%
  • Code gen −90%
  • Agentic −88%
  • no file input
Gemini 3.8 Flash Google1497 +51.4$3.00
  • Balanced −25%
  • Summarise −24%
  • Chat −25%
  • Code gen −25%
  • Agentic −23%
  • 1.1M → 1M context
  • 128K → 66K max output
Muse Spark 1.3 Meta1489.9 +44.3$2.00
  • Balanced −50%
  • Summarise −42%
  • Chat −54%
  • Code gen −55%
  • Agentic −49%
  • 1.1M → 1M context
Gemini 3.7 Flash Google1487 +41.4$3.00
  • Balanced −25%
  • Summarise −24%
  • Chat −25%
  • Code gen −25%
  • Agentic −23%
  • 1.1M → 1M context
  • 128K → 66K max output
Muse Spark 1.2 Meta1483.2 +37.6$2.00
  • Balanced −50%
  • Summarise −42%
  • Chat −54%
  • Code gen −55%
  • Agentic −49%
  • 1.1M → 1M context
Gemini 3.6 Flash Google1479.5 +33.9$1.50
  • Balanced −63%
  • Summarise −62%
  • Chat −62%
  • Code gen −62%
  • Agentic −61%
  • 1.1M → 1M context
  • 128K → 66K max output
Muse Spark 1.1 Meta1479.2 +33.6$2.00
  • Balanced −50%
  • Summarise −42%
  • Chat −54%
  • Code gen −55%
  • Agentic −49%
  • 1.1M → 1M context
Gemini 3.5 Flash Google1477.7 +32.1$3.38
  • Balanced −16%
  • Summarise −20%
  • Chat −12%
  • Code gen −11%
  • Agentic −12%
  • 1.1M → 1M context
  • 128K → 66K max output
GLM 5.3 Flash Z.ai1469.6 +24$0.238
  • Balanced −94%
  • Summarise −93%
  • Chat −95%
  • Code gen −95%
  • Agentic −94%
  • 1.1M → 1M context
  • no file input
GLM 5.3 Z.ai1471.4 +25.8$1.00
  • Balanced −75%
  • Summarise −81%
  • Chat −68%
  • Code gen −68%
  • Agentic −69%
  • 1.1M → 1M context
  • no file, image input
GLM 5.2 Z.ai1470.4 +24.8$1.12
  • Balanced −72%
  • Summarise −77%
  • Chat −66%
  • Code gen −66%
  • Agentic −67%
  • 1.1M → 1M context
  • no file, image input
Kimi K3 Moonshot AI1475.9 +30.3$3.76
  • Balanced −6%
  • Summarise −34%
  • 1.1M → 1M context
  • no file input
MiMo-V2.5-Pro Xiaomi1465 +19.4$0.544
  • Balanced −86%
  • Summarise −82%
  • Chat −90%
  • Code gen −90%
  • Agentic −88%
  • no file, image input
DeepSeek V4.1 Flash DeepSeek1462.5 +16.9$0.182
  • Balanced −95%
  • Summarise −96%
  • Chat −95%
  • Code gen −95%
  • Agentic −95%
  • 1.1M → 1M context
  • no file input
GLM 5.1 Z.ai1461.5 +15.9$1.83
  • Balanced −54%
  • Summarise −38%
  • Chat −56%
  • Code gen −60%
  • Agentic −41%
  • 1.1M → 205K context
  • no file, image input
Claude Sonnet 5.5 Anthropic1466.6 +21$4.00
  • Balanced same price
  • 1.1M → 1M context
MiMo-V2.6-Flash Xiaomi1456.4 +10.8$0.175
  • Balanced −96%
  • Summarise −94%
  • Chat −97%
  • Code gen −97%
  • Agentic −96%
  • no file input
Qwen3.7 Plus Qwen1454.6 tie$0.560
  • Balanced −86%
  • Summarise −84%
  • Chat −86%
  • Code gen −87%
  • Agentic −85%
  • 1.1M → 1M context
  • no file input
Kimi K2.6 Moonshot AI1455.5 tie$0.961
  • Balanced −76%
  • Summarise −75%
  • Chat −75%
  • Code gen −76%
  • Agentic −74%
  • 1.1M → 262K context
  • no file input
Gemini 2.5 Pro Google1457.8 +12.2$3.44
  • Balanced −14%
  • Summarise −26%
  • Chat −5%
  • Code gen −4%
  • Agentic −9%
  • 1.1M → 1M context
  • 128K → 66K max output
GLM 5 Z.ai1446.3 tie$1.09
  • Balanced −73%
  • Summarise −67%
  • Chat −75%
  • Code gen −76%
  • Agentic −71%
  • 1.1M → 205K context
  • no file, image input
Qwen3.6 Max Preview Qwen1446.8 tie$2.31
  • Balanced −42%
  • Summarise −31%
  • Chat −33%
  • Code gen −38%
  • Agentic −13%
  • 1.1M → 262K context
  • 128K → 66K max output
  • no file, image input
Grok 4.5 xAI1448.1 tie$3.00
  • Balanced −25%
  • Summarise −8%
  • Chat −33%
  • Code gen −36%
  • Agentic −23%
  • 1.1M → 500K context

What this compares, and what it leaves out

  • Quality is LMArena Elo, used under CC BY 4.0 from the official dataset. The 95% confidence interval on a difference between two scores is about ±10.47 points, so a gap smaller than that is marked tie rather than an improvement — see significance bands.
  • 204 further models at this delivery mode carry a price but no independent score. They are absent from the comparison in both directions — unrated is not a zero, and an unmeasured model is neither an alternative nor a worse buy.
  • Retired models are never offered as an alternative, and a model only competes against its own delivery mode: batch trades latency for price, so it is not a like-for-like swap.
  • Nothing here measures latency, throughput, rate limits or how a model behaves on your prompts. Two models with the same index score are not interchangeable.
  • Models with no higher-scoring or cheaper alternative that is no worse on the other axis are on the value frontier. Models with such an alternative are listed here.
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