phi-4 vs GPT-5.1

At a Glance

Compare
phi-4Microsoft
GPT-5.1OpenAI
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5UnrankedNot in the 46-model eligible cohort#37 of 4625.7 score · 2/3 sources · provisional · missing LiveBench · full-core range 17.1–50.5
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.070Deepinfra · Sep 22, 2026$1.25Openai · Sep 3, 2026
Output priceFrom · USD / 1M tokens$0.14Deepinfra · Sep 22, 2026$10.00Openai · Sep 3, 2026
Context windowMaximum documented tokens16K400K
Model facts checkedAug 28, 2026View model evidence →Sep 3, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Available Benchmarks

All benchmark results →
Benchmarkphi-4GPT-5.1
LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader1,216.6086% of row best · rating · phi-4; 95% CI [1212.02298793, 1221.18318193]; votes 24126; rank 3001,422.57100% of row best · rating · gpt-5.1; 95% CI [1418.95842118, 1426.18777801]; votes 42982; rank 100
Overall ResultCounted from the protocol-matched rows above0 benchmark winsNo overall winner1 benchmark winNo overall winner

Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.

Side-by-Side Facts

Fieldphi-4GPT-5.1
DeveloperMicrosoftOpenAI
FamilyPhi 4Gpt 5 1
Modelphi-4GPT-5.1
Versionphi-4GPT-5.1
Lifecycleactiveactive
Released2024-12-122025-11-13
Knowledge cutoffUnknown2024-09-30
Input modalitiesTextText, Image
Output modalitiesTextText
Context window16K400K
Total parameters14.7BUnknown
Active parametersUnknownUnknown
LicensemitUnknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)Openai (Standard), Openrouter (Standard)
Capabilitieschat, generationchat, generation, reasoning, structured_outputs, tools

phi-4 Capabilities

chatgeneration
Serving providers3
Canonical IDmicrosoft/phi-4

GPT-5.1 Capabilities

chatgenerationreasoningstructured outputstools
Serving providers2
Canonical IDopenai/gpt-5.1

Primary Evidence

Sources and Freshness

Questions

phi-4 vs GPT-5.1 FAQs

Is phi-4 or GPT-5.1 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both phi-4 and GPT-5.1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, phi-4 or GPT-5.1?+

phi-4 is $0.070 and GPT-5.1 is $1.25 per million tokens, so phi-4 is cheaper on this metric. phi-4 is $0.14 and GPT-5.1 is $10.00 per million tokens, so phi-4 is cheaper on this metric.

Which has a larger context window, phi-4 or GPT-5.1?+

GPT-5.1 has the larger sourced context window. phi-4 supports 16K and GPT-5.1 supports 400K.

Which performs better in benchmarks, phi-4 or GPT-5.1?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can phi-4 or GPT-5.1 be self-hosted?+

phi-4 is the only model in this pair currently marked as self-hostable. phi-4 is open weight; GPT-5.1 is not marked open weight.

Can phi-4 and GPT-5.1 understand images?+

phi-4 is not documented with image input; GPT-5.1 is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, phi-4 or GPT-5.1?+

Neither has a larger sourced maximum output. phi-4 is — and GPT-5.1 is 128K.

Do phi-4 and GPT-5.1 support reasoning and tool use?+

phi-4: none of these features are definitively sourced. GPT-5.1: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, phi-4 or GPT-5.1?+

phi-4 has 3 sourced provider routes; GPT-5.1 has 2, so phi-4 has broader tracked availability.

Which offers better value, phi-4 or GPT-5.1?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

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