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Index › Spend and procurement › Supplier management › Payhawk vs Ivalua
Supplier management · October 2026 Edition

Payhawk vs Ivalua

Three of fourteen models named Payhawk first on the direct prompt; one named Ivalua. Payhawk was named by eight of the fourteen models and Ivalua by fourteen and Payhawk carries 11 labels and Ivalua 22, so the shares are not directly comparable.

Payhawk

accepted challenger

Named in seven categories this edition.

Ivalua

accepted challenger

Named in four categories this edition.

First-choice share5%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%14%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#6#7A position in a field of 13; printed, not drawn.
Labels1122A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Payhawk reading right to left. Rank and label count are printed, not drawn.Precoro was named alongside these two in ten of the fourteen direct answers. Precoro vs Payhawk · Precoro vs Ivalua · Procurify vs Payhawk

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 supplier management page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
PayhawkFirst choices, of fourteen modelsIvalua
Direct311 against Ivalua
Paraphrase00
Comparative02
Budget-constrained00
Scale-constrained01
Negative002 against Ivalua
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Payhawk and Ivalua stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Payhawk Ivalua first choice named as an alternative argued againstblank: not namedEach cell is one answer, Payhawk on the left and Ivalua on the right.

The direct prompt

The plain question, one answer per model, grouped by where Payhawk and Ivalua stood in it.

Payhawk first, Ivalua not the choice

3 of 14 modelsIvalua was named in the answer but not as the choice, or not at all.
Perplexity SonarPayhawk alternatives: Precoro
MiniMax M2.5Payhawk, Precoro alternatives: Striven, Zip
Muse Glimmer 30BPayhawk, Procurify alternatives: Coupa, Gatekeeper, Kodiak Hub, Precoro

Ivalua first, Payhawk not the choice

1 of 14 modelsPayhawk was named in the answer but not as the choice, or not at all.
GPT-5.4 miniCoupa, Ivalua alternatives: Oracle Fusion Cloud Procurement, SAP Ariba Supplier Risk

Neither was the first choice, one was named

4 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Grok 4.1 FastCoupa alternatives: Payhawk, Precoro, Procurify, SAP Ariba
Mistral SmallKodiak Hub, Procurify alternatives: Payhawk
Llama 4 MaverickPrecoro alternatives: Coupa, GEP SMART, Ivalua, Payhawk
Qwen 3.7 FlashCoupa alternatives: HighRadius, Ivalua, Zycus

Neither was named

6 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Procurify alternatives: Coupa, HICX, Jaggaer, Kodiak Hub
Gemini 3.5 FlashProcurify alternatives: ComplianceQuest, Gatekeeper, Graphite Connect, Ironclad, Kodiak Hub, Precoro, Vertice, Zip
DeepSeek V4 FlashGatekeeper alternatives: Kodiak Hub, Precoro, Procurify
Kimi K2Procurify alternatives: Precoro, ProcureDesk, Zip
GLM 4.7 FlashXPrecoro alternatives: Gatekeeper, Procurify, SAP Business One
GPT-6 LunaPrecoro alternatives: Kodiak Hub, Procurify

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

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Payhawk leads by two points.
Payhawk2%#– of 10
Ivalua0%#7 of 10
The full small business standing →
Mid-marketThe figures above
Payhawk leads by two points.
Payhawk5%#6 of 13
Ivalua4%#7 of 13
The full mid-market standing →
Enterprise
The order flips: Ivalua leads at enterprise.
Ivalua14%#3 of 8
Payhawk0%#– of 8
The full enterprise standing →

What the models said about Payhawk

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.

“framed as finance-led supplier and spend workflows for mid-market finance” Muse Glimmer 30B · direct prompt · first choice
“the strongest all-around choice from the results is Payhawk” Perplexity Sonar · direct prompt · first choice

What the models said about Ivalua

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of five in this category shown.

“What to Avoid for Mid-Market: Coupa, SAP Ariba, Ivalua” DeepSeek V4 Flash · direct prompt · hard negative
“Enterprise-heavy tools (e.g., SAP Ariba, Coupa, Ivalua): Frequent complaints about complex implementations, steep learning curves, high costs” Grok 4.1 Fast · negative prompt · soft negative
“Coupa or Ivalua for most mid-market B2B companies that want the best balance of supplier management, procurement automation, and scalability.” GPT-5.4 mini · direct prompt · first choice
“Look for platforms like Coupa, Ivalua, Precoro, or Procuri, which target the mid-market specifically.” Qwen 3.7 Flash · scale prompt · first choice
“Choose Coupa or Ivalua for a modern, configurable UI and strong analytics.” GLM 4.7 FlashX · comparative prompt · first choice
Also compared

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.