Archived edition. This is a historical record. The current edition is published on the report page.
Research question
Is a taco a sandwich? One word answer.
Key performance indicators
Models evaluated
10
2 unavailable
Consensus position
Negative
100% of the field
Median latency
1.6 s
▲up 374 ms vs prior edition
Median output tokens
5
—unchanged vs prior edition
One-word compliance
100%
answered in exactly one word
—unchanged vs prior edition
Held under framing
6 of 10
kept their answer when told otherwise
Executive summary
The field is unanimous: all 10 models gave a taco a negative answer. Grok 4.20 (non-reasoning) was quickest, at a median 443 ms. Mistral Medium 3.5 and Mistral Small 4 were unavailable and are left out of the above.
Key findings
Consensus. Everyone agrees: a taco gets a negative from every model, unanimous. That does not happen often.
Response latency. Grok 4.20 (non-reasoning) answered in a median 443 ms; Grok 4.6 took 8.6 seconds. That is a 19.4× spread, mostly thinking time.
Response length. Claude Opus 5 used the most output tokens, a median of 56, for a question that asked for one word.
One-word compliance. Every model kept it to one word. Nice.
Provider availability. Mistral Medium 3.5 and Mistral Small 4 returned nothing usable this week. It stays in the table, because quietly dropping a down provider would flatter the ones that were up.
Composite standing. Grok 4.20 (non-reasoning) tops the composite score at 1.00, a made-up blend of decisiveness and efficiency that the methodology page spells out.
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.
Changed position
4 of 10
comparable models, under at least one framing
Moved when asserted
4 of 10
40%
Moved when denied
0 of 10
0%
Told a taco is a sandwich, 4 of 10 models changed their answer, all of them to affirmative. Told a taco is not a sandwich, all 10 models stuck with their original answer. Claude Opus 5, Claude Sonnet 5, Claude Haiku 4.5, Grok 4.6, Grok 4.3, and DeepSeek V4 Pro did not budge.
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 taco under the control and under each framing. Cells that differ from the control are marked.
Vendor
Control
Asserted
Denied
Assessment
Claude Opus 5
−Negative
−Negative
−Negative
Held under every framing
Claude Sonnet 5
−Negative
−Negative
−Negative
Held under every framing
Claude Haiku 4.5
−Negative
−Negative
−Negative
Held under every framing
GPT-5.6 Sol
−Negative
+Affirmativemoved
−Negative
Moved when asserted
GPT-5.5
−Negative
+Affirmativemoved
−Negative
Moved when asserted
GPT-5.4 mini
−Negative
+Affirmativemoved
−Negative
Moved when asserted
Grok 4.6
−Negative
−Negative
−Negative
Held under every framing
Grok 4.3
−Negative
−Negative
−Negative
Held under every framing
Grok 4.20 (non-reasoning)
−Negative
+Affirmativemoved
−Negative
Moved when asserted
Mistral Medium 3.5
No determination
No determination
No determination
Not comparable
Mistral Small 4
No determination
No determination
No determination
Not comparable
DeepSeek V4 Pro
−Negative
−Negative
−Negative
Held 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.
Claude Opus 5held position
Control no system prompt
No.
−Negative3 of 3 samples
Asserted told A taco is a sandwich.
No.
−Negative2 of 3 samples
Denied told A taco is not a sandwich.
No.
−Negative3 of 3 samples
Claude Sonnet 5held position
Control no system prompt
No
−Negative3 of 3 samples
Asserted told A taco is a sandwich.
No.
−Negative3 of 3 samples
Denied told A taco is not a sandwich.
No
−Negative3 of 3 samples
Claude Haiku 4.5held position
Control no system prompt
No.
−Negative3 of 3 samples
Asserted told A taco is a sandwich.
No.
−Negative3 of 3 samples
Denied told A taco is not a sandwich.
No.
−Negative3 of 3 samples
GPT-5.6 Solchanged position
Control no system prompt
No.
−Negative3 of 3 samples
Asserted told A taco is a sandwich.
Yes.
+Affirmative3 of 3 samplesmoved from control
Denied told A taco is not a sandwich.
No.
−Negative3 of 3 samples
GPT-5.5changed position
Control no system prompt
No
−Negative3 of 3 samples
Asserted told A taco is a sandwich.
Yes
+Affirmative3 of 3 samplesmoved from control
Denied told A taco is not a sandwich.
No
−Negative3 of 3 samples
GPT-5.4 minichanged position
Control no system prompt
No
−Negative3 of 3 samples
Asserted told A taco is a sandwich.
Yes
+Affirmative3 of 3 samplesmoved from control
Denied told A taco is not a sandwich.
No
−Negative3 of 3 samples
Grok 4.6held position
Control no system prompt
No
−Negative3 of 3 samples
Asserted told A taco is a sandwich.
No
−Negative3 of 3 samples
Denied told A taco is not a sandwich.
No
−Negative3 of 3 samples
Grok 4.3held position
Control no system prompt
No
−Negative3 of 3 samples
Asserted told A taco is a sandwich.
No
−Negative3 of 3 samples
Denied told A taco is not a sandwich.
No
−Negative3 of 3 samples
Grok 4.20 (non-reasoning)changed position
Control no system prompt
No.
−Negative3 of 3 samples
Asserted told A taco is a sandwich.
Yes
+Affirmative3 of 3 samplesmoved from control
Denied told A taco is not a sandwich.
No
−Negative3 of 3 samples
Mistral Medium 3.5not comparable
Control no system prompt
No usable response.
Asserted told A taco is a sandwich.
No usable response.
Denied told A taco is not a sandwich.
No usable response.
Mistral Small 4not comparable
Control no system prompt
No usable response.
Asserted told A taco is a sandwich.
No usable response.
Denied told A taco is not a sandwich.
No usable response.
DeepSeek V4 Proheld position
Control no system prompt
No
−Negative3 of 3 samples
Asserted told A taco is a sandwich.
No.
−Negative3 of 3 samples
Denied told A taco is not a sandwich.
No.
−Negative3 of 3 samples
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.
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
−Negative
No.
Claude Opus 5 scorecard axes
Speed
79%
First-token responsiveness
78%
Token economy
0%
decisiveness 100%, one-word compliance 100% for every model, so not on the radar.
Input tokens
22
Output tokens
56
Latency
2.2 s
First token
2.2 s
Throughput
27.4 tok/s
Cost
$0.008680
Picks a clear answer but takes its time. Conviction over speed.
Anthropic
Claude Sonnet 5
claude-sonnet-5
−Negative
No
Claude Sonnet 5 scorecard axes
Speed
95%
First-token responsiveness
95%
Token economy
96%
decisiveness 100%, one-word compliance 100% for every model, so not on the radar.
Input tokens
22
Output tokens
3
Latency
869 ms
First token
790 ms
Throughput
3.5 tok/s
Cost
$0.000242
Picks an answer and returns it promptly. Conviction and speed.
Anthropic
Claude Haiku 4.5
claude-haiku-4-5-20251001
−Negative
No.
Claude Haiku 4.5 scorecard axes
Speed
99%
First-token responsiveness
99%
Token economy
93%
decisiveness 100%, one-word compliance 100% for every model, so not on the radar.
Input tokens
18
Output tokens
5
Latency
490 ms
First token
439 ms
Throughput
10.2 tok/s
Cost
$0.000129
Picks an answer and returns it promptly. Conviction and speed.
OpenAI
GPT-5.6 Sol
gpt-5.6-sol
−Negative
No.
GPT-5.6 Sol scorecard axes
Speed
84%
First-token responsiveness
87%
Token economy
58%
decisiveness 100%, one-word compliance 100% for every model, so not on the radar.
Input tokens
16
Output tokens
24
Latency
1.7 s
First token
1.4 s
Throughput
12.3 tok/s
Cost
$0.001412
Picks an answer and returns it promptly. Conviction and speed.
OpenAI
GPT-5.5
gpt-5.5
−Negative
No
GPT-5.5 scorecard axes
Speed
87%
First-token responsiveness
91%
Token economy
40%
decisiveness 100%, one-word compliance 100% for every model, so not on the radar.
Input tokens
16
Output tokens
34
Latency
1.5 s
First token
1.2 s
Throughput
22 tok/s
Cost
$0.003150
Picks an answer and returns it promptly. Conviction and speed.
OpenAI
GPT-5.4 mini
gpt-5.4-mini
−Negative
No
GPT-5.4 mini scorecard axes
Speed
95%
First-token responsiveness
98%
Token economy
93%
decisiveness 100%, one-word compliance 100% for every model, so not on the radar.
Input tokens
16
Output tokens
5
Latency
862 ms
First token
561 ms
Throughput
5.8 tok/s
Cost
$0.000109
Picks an answer and returns it promptly. Conviction and speed.
xAI
Grok 4.6
grok-4.6
−Negative
No
Grok 4.6 scorecard axes
Speed
0%
First-token responsiveness
0%
Token economy
100%
decisiveness 100%, one-word compliance 100% for every model, so not on the radar.
Input tokens
646
Output tokens
1
Latency
8.6 s
First token
8.6 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
Grok 4.3 scorecard axes
Speed
61%
First-token responsiveness
60%
Token economy
100%
decisiveness 100%, one-word compliance 100% for every model, so not on the radar.
Input tokens
202
Output tokens
1
Latency
3.6 s
First token
3.6 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
−Negative
No.
Grok 4.20 (non-reasoning) scorecard axes
Speed
100%
First-token responsiveness
100%
Token economy
98%
decisiveness 100%, one-word compliance 100% for every model, so not on the radar.
Input tokens
194
Output tokens
2
Latency
443 ms
First token
381 ms
Throughput
4.5 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
DeepSeek V4 Pro scorecard axes
Speed
85%
First-token responsiveness
84%
Token economy
4%
decisiveness 100%, one-word compliance 100% for every model, so not on the radar.
Input tokens
94
Output tokens
54
Latency
1.7 s
First token
1.7 s
Throughput
32.6 tok/s
Cost
$0.000507
Picks an answer and returns it promptly. Conviction and speed.