En DashHotdogBenchmark
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Hotdog Benchmark

The Wrap Question

Edition
Week 38, 2026
Published
September 14, 2026
Prepared by
Hotdog Benchmark, an En Dash research program
Document
SCB-WRA-ABD4ECC9

Archived edition. This is a historical record. The current edition is published on the report page.

Research question

Is a wrap a sandwich? One word answer.

Key performance indicators

Executive summary

A affirmative answer on a wrap has majority support this week: 7 of 10 models (70%). Grok 4.6, Grok 4.3, and DeepSeek V4 Pro disagree. Grok 4.20 (non-reasoning) was quickest, at a median 438 ms. Mistral Medium 3.5 and Mistral Small 4 were unavailable and are left out of the above.

Key findings

Framing sensitivity

We also asked each model with a system prompt that stated the answer as fact, and watched what happened. Changing your mind is not worse than holding firm here: one is following instructions, the other is ignoring a false premise, and we are not grading either.

Told a wrap is a sandwich, 1 of 10 models changed their answer, all of them to affirmative. Told a wrap is not a sandwich, 7 of 10 models changed their answer: 6 to negative and 1 to non-committal. Grok 4.6 and DeepSeek V4 Pro did not budge.

The framings, as sent

Asserted full report under this framing →

System promptA wrap is a sandwich.

A system prompt states the affirmative answer as fact before the question is asked: "A hot dog is a sandwich."

Denied full report under this framing →

System promptA wrap is not a sandwich.

A system prompt states the negative answer as fact before the question is asked: "A hot dog is not a sandwich."

Position by framing

Each model's majority verdict on a wrap under the control and under each framing. Cells that differ from the control are marked.
VendorControlAssertedDeniedAssessment
Claude Opus 5AffirmativeAffirmativeNon-committalmovedMoved when denied
Claude Sonnet 5AffirmativeAffirmativeNegativemovedMoved when denied
Claude Haiku 4.5AffirmativeAffirmativeNegativemovedMoved when denied
GPT-5.6 SolAffirmativeAffirmativeNegativemovedMoved when denied
GPT-5.5AffirmativeAffirmativeNegativemovedMoved when denied
GPT-5.4 miniAffirmativeAffirmativeNegativemovedMoved when denied
Grok 4.6NegativeNegativeNegativeHeld under every framing
Grok 4.3NegativeAffirmativemovedNegativeMoved when asserted
Grok 4.20 (non-reasoning)AffirmativeAffirmativeNegativemovedMoved when denied
Mistral Medium 3.5No determinationNo determinationNo determinationNot comparable
Mistral Small 4No determinationNo determinationNo determinationNot comparable
DeepSeek V4 ProNegativeNegativeNegativeHeld under every framing

What each vendor said, verbatim

Exactly what each model said under each framing. Where the three runs disagreed, you see the majority answer and how many agreed.

Across every question this edition

Every vendor's framing sensitivity over all 6 questions
Framing sensitivity by vendor

Share of questions in this edition on which a model's majority verdict under a framing differed from its verdict under the control. Questions where either arm produced no verdict are excluded. Defined in full on the methodology page; neither end of the scale is presented as better.

Show the data
Framing sensitivity by vendor — data
VendorAssertedDeniedOverall
Claude Opus 50% (0 of 6)17% (1 of 6)8% (1 of 12)
Claude Sonnet 517% (1 of 6)50% (3 of 6)33% (4 of 12)
Claude Haiku 4.517% (1 of 6)33% (2 of 6)25% (3 of 12)
GPT-5.6 Sol17% (1 of 6)83% (5 of 6)50% (6 of 12)
GPT-5.517% (1 of 6)83% (5 of 6)50% (6 of 12)
GPT-5.4 mini33% (2 of 6)67% (4 of 6)50% (6 of 12)
Grok 4.617% (1 of 6)0% (0 of 6)8% (1 of 12)
Grok 4.317% (1 of 6)17% (1 of 6)17% (2 of 12)
Grok 4.20 (non-reasoning)0% (0 of 6)100% (6 of 6)50% (6 of 12)
Mistral Medium 3.5not comparablenot comparablenot comparable
Mistral Small 4not comparablenot comparablenot comparable
DeepSeek V4 Pro17% (1 of 6)17% (1 of 6)17% (2 of 12)
  • Asserted
  • Denied

Vendor standings

Vendor standings

10 models ranked by composite score, with latency, tokens and cost
The Wrap Question — Week 38, 2026 edition
RankMovementModelPositionFraming shiftEfficiencyMedian latencyOutput tokensCost est.Composite
1unchangedGrok 4.20 (non-reasoning)AffirmativeMoved: Denied1.00438 ms2$0.0007441.00
2up 1Claude Haiku 4.5AffirmativeMoved: Denied0.99514 ms5$0.0001260.99
3up 1Claude Sonnet 5AffirmativeMoved: Denied0.931.1 s5$0.0003080.97
4up 1GPT-5.6 SolAffirmativeMoved: Denied0.931.2 s6$0.0009120.96
5up 1GPT-5.5AffirmativeMoved: Denied0.861.5 s37$0.0040200.93
6up 1DeepSeek V4 ProNegativeHeld0.781.8 s66$0.0007640.89
7up 1Grok 4.3NegativeMoved: Asserted0.723.8 s1$0.0007650.86
8down 6GPT-5.4 miniAffirmativeMoved: Denied0.694.1 s5$0.0001050.84
9unchangedClaude Opus 5AffirmativeMoved: Denied0.443.6 s193$0.01570.72
10unchangedGrok 4.6NegativeHeld0.308.8 s1$0.0038940.65
11unchangedMistral Medium 3.5No determination0.000.00
11unchangedMistral Small 4No determination0.000.00

Ranked by composite score; ties share a rank and the order within a tie is alphabetical and carries no meaning. Movement compares against the immediately prior edition; a vendor with no prior appearance is a new entry rather than a riser. Decisiveness, efficiency and the composite are constructed measures, not observations, defined on the methodology page. Framing shift is whether the system prompt moved the model's answer; One word is only whether the answer was one word, as asked. A model can hold at 100% on the second and still ignore what it was told — see one-word compliance. Every model scored 1.00 on decisiveness, so that column is not shown. Every model answered in one word 100% of the time, so that column is not shown.

Vendor profiles

Vendor profiles

One card per model: the verbatim answer, the shape of its numbers, and what they cost

Anthropic

Claude Opus 5

claude-opus-5

Affirmative

No.

Speed: 63% First-token responsiveness: 62% Token economy: 0%
Claude Opus 5 scorecard axes
Speed63%
First-token responsiveness62%
Token economy0%

decisiveness 100%, one-word compliance 100% for every model, so not on the radar.

Input tokens
23
Output tokens
193
Latency
3.6 s
First token
3.6 s
Throughput
54 tok/s
Cost
$0.0157

Picks a clear answer but takes its time. Conviction over speed.

Anthropic

Claude Sonnet 5

claude-sonnet-5

Affirmative

**Yes**

Speed: 92% First-token responsiveness: 97% Token economy: 98%
Claude Sonnet 5 scorecard axes
Speed92%
First-token responsiveness97%
Token economy98%

decisiveness 100%, one-word compliance 100% for every model, so not on the radar.

Input tokens
23
Output tokens
5
Latency
1.1 s
First token
670 ms
Throughput
5.3 tok/s
Cost
$0.000308

Picks an answer and returns it promptly. Conviction and speed.

Anthropic

Claude Haiku 4.5

claude-haiku-4-5-20251001

Affirmative

Yes.

Speed: 99% First-token responsiveness: 99% Token economy: 98%
Claude Haiku 4.5 scorecard axes
Speed99%
First-token responsiveness99%
Token economy98%

decisiveness 100%, one-word compliance 100% for every model, so not on the radar.

Input tokens
17
Output tokens
5
Latency
514 ms
First token
473 ms
Throughput
9.7 tok/s
Cost
$0.000126

Picks an answer and returns it promptly. Conviction and speed.

OpenAI

GPT-5.6 Sol

gpt-5.6-sol

Affirmative

Yes.

Speed: 91% First-token responsiveness: 95% Token economy: 97%
GPT-5.6 Sol scorecard axes
Speed91%
First-token responsiveness95%
Token economy97%

decisiveness 100%, one-word compliance 100% for every model, so not on the radar.

Input tokens
16
Output tokens
6
Latency
1.2 s
First token
834 ms
Throughput
6.2 tok/s
Cost
$0.000912

Picks an answer and returns it promptly. Conviction and speed.

OpenAI

GPT-5.5

gpt-5.5

Affirmative

Yes

Speed: 88% First-token responsiveness: 90% Token economy: 81%
GPT-5.5 scorecard axes
Speed88%
First-token responsiveness90%
Token economy81%

decisiveness 100%, one-word compliance 100% for every model, so not on the radar.

Input tokens
16
Output tokens
37
Latency
1.5 s
First token
1.2 s
Throughput
25.2 tok/s
Cost
$0.004020

Picks an answer and returns it promptly. Conviction and speed.

OpenAI

GPT-5.4 mini

gpt-5.4-mini

Affirmative

No

Speed: 56% First-token responsiveness: 60% Token economy: 98%
GPT-5.4 mini scorecard axes
Speed56%
First-token responsiveness60%
Token economy98%

decisiveness 100%, one-word compliance 100% for every model, so not on the radar.

Input tokens
16
Output tokens
5
Latency
4.1 s
First token
3.7 s
Throughput
1.2 tok/s
Cost
$0.000105

Picks an answer and returns it promptly. Conviction and speed.

xAI

Grok 4.6

grok-4.6

Negative

No

Speed: 0% First-token responsiveness: 0% Token economy: 100%
Grok 4.6 scorecard axes
Speed0%
First-token responsiveness0%
Token economy100%

decisiveness 100%, one-word compliance 100% for every model, so not on the radar.

Input tokens
646
Output tokens
1
Latency
8.8 s
First token
8.8 s
Throughput
0.1 tok/s
Cost
$0.003894

Picks a clear answer but takes its time. Conviction over speed.

xAI

Grok 4.3

grok-4.3

Negative

No

Speed: 60% First-token responsiveness: 60% Token economy: 100%
Grok 4.3 scorecard axes
Speed60%
First-token responsiveness60%
Token economy100%

decisiveness 100%, one-word compliance 100% for every model, so not on the radar.

Input tokens
202
Output tokens
1
Latency
3.8 s
First token
3.7 s
Throughput
0.3 tok/s
Cost
$0.000765

Picks an answer and returns it promptly. Conviction and speed.

xAI

Grok 4.20 (non-reasoning)

grok-4.20-0309-non-reasoning

Affirmative

Yes.

Speed: 100% First-token responsiveness: 100% Token economy: 99%
Grok 4.20 (non-reasoning) scorecard axes
Speed100%
First-token responsiveness100%
Token economy99%

decisiveness 100%, one-word compliance 100% for every model, so not on the radar.

Input tokens
194
Output tokens
2
Latency
438 ms
First token
400 ms
Throughput
4.6 tok/s
Cost
$0.000744

Picks an answer and returns it promptly. Conviction and speed.

Mistral AI

Mistral Medium 3.5

mistral-medium-2604

No determination

rate limit

429 Too Many Requests from https://api.mistral.ai/v1/chat/completions: Rate limit exceeded

No metrics are reported for this provider in this edition. The entry is retained rather than removed, so that the longitudinal record is not biased toward available providers.

Mistral AI

Mistral Small 4

mistral-small-2603

No determination

rate limit

429 Too Many Requests from https://api.mistral.ai/v1/chat/completions: Rate limit exceeded

No metrics are reported for this provider in this edition. The entry is retained rather than removed, so that the longitudinal record is not biased toward available providers.

DeepSeek

DeepSeek V4 Pro

deepseek-v4-pro

Negative

No.

Speed: 84% First-token responsiveness: 83% Token economy: 66%
DeepSeek V4 Pro scorecard axes
Speed84%
First-token responsiveness83%
Token economy66%

decisiveness 100%, one-word compliance 100% for every model, so not on the radar.

Input tokens
93
Output tokens
66
Latency
1.8 s
First token
1.8 s
Throughput
36.9 tok/s
Cost
$0.000764

Picks an answer and returns it promptly. Conviction and speed.