Soda vs Bigeye
One of fourteen models named Soda first on the direct prompt; one named Bigeye. Both were named by all fourteen models and Soda carries 42 labels and Bigeye 35, so the shares are not directly comparable.
Named in one category this edition.
Named in one category this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the data quality and observability page.
By framing
SodaFirst choices, of fourteen modelsBigeye
Across every category in the October 2026 Edition, Soda and Bigeye were named in the same answer sixty times, of the 106 answers naming Soda and the 105 naming Bigeye. In those answers Bigeye took the first choice four times and Soda eight.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | | | ||
| GPT-5.4 mini | | | | | ||
| Gemini 3.5 Flash | | | | | | |
| Perplexity Sonar | | | ||||
| Grok 4.1 Fast | | | | |||
| Mistral Small | | |||||
| DeepSeek V4 Flash | | | | | | |
| Llama 4 Maverick | | |||||
| Qwen 3.7 Flash | | | | | ||
| Kimi K2 | | | | | ||
| GLM 4.7 FlashX | | | ||||
| MiniMax M2.5 | | | | |||
| GPT-6 Luna | | | ||||
| Muse Glimmer 30B | | | | | |
Soda Bigeye first choice named as an alternative argued againstblank: not namedEach cell is one answer, Soda on the left and Bigeye on the right.The direct prompt
Soda first, Bigeye an alternative
1 of 14 modelsBigeye was named in the answer but not as the choice, or not at all.Bigeye first, Soda not the choice
1 of 14 modelsSoda was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
9 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
3 of 14 modelsThe answer made no first choice from these two in this category.Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
By buyer segment
What the models said about Soda
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Why be cautious: if you plan to stay on Soda Core open-source, assess ongoing support and feature parity; Soda Cloud pricing and roadmap are not self-serve” Muse Glimmer 30B · negative prompt · soft negative
“License change risk... Not full observability... Limited out-of-the-box metrics.” DeepSeek V4 Flash · negative prompt · soft negative
“Soda might require more upfront effort to configure tests” Claude Haiku 4.5 · negative prompt · soft negative
“Soda is often the better default because mid-sized teams usually benefit from faster adoption and built-in observability” GPT-5.4 mini · paraphrase prompt · first choice
“I'd shortlist Soda. It offers checks and monitoring across common warehouses and databases” GPT-6 Luna · paraphrase prompt · first choice
“best value choice is usually Great Expectations (GX Core) or Soda Free/open-source first” GPT-5.4 mini · budget prompt · first choice
What the models said about Bigeye
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Why be cautious: integration gaps for non-standard stacks, workspace management overhead, and enterprise-only quote pricing.” Muse Glimmer 30B · negative prompt · soft negative
“users note tuning needs; consolidation (e.g., via acquisitions like Datadog/Metaplane) may disrupt roadmaps” Grok 4.1 Fast · negative prompt · soft negative
“Monte Carlo, Anomalo, Bigeye: While popular, these ML-based platforms are best for specific use cases” Mistral Small · negative prompt · soft negative
“Bigeye is positioned as the Enterprise AI Trust Platform combining data observability, end-to-end lineage and agentic AI governance. It is recommended for large enterprises 500+ employees” Muse Glimmer 30B · scale prompt · first choice
“Bigeye is the platform most guides explicitly call out for mid-market ease of use and quick implementation” Muse Glimmer 30B · direct prompt · first choice
“If you want production observability with automated anomaly detection: Monte Carlo or Bigeye” GPT-5.4 mini · comparative prompt · first choice
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.