Phi-4 Multimodal Instruct vs Grok 4.6

Model Markets Rankings

Intelligence, Cost, and Efficiency

All rankings →
RankingPhi-4-multimodal-instructGrok 4.6
CostLower is better · Published-token output estimateUnrankedNot in the 36-model eligible cohort#18 of 36$0.097 per LiveBench case

Ranks come from the current complete eligible cohorts. Green highlights appear only when both models are ranked in the same metric. Missing required inputs remain unranked, and the three dimensions are not collapsed into an overall winner.

Benchmark Performance

Available Benchmarks

No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.
FieldAt a Glance
Microsoft · activePhi-4 Multimodal InstructVerified Aug 28, 2026
xAI · activeGrok 4.6Verified Aug 29, 2026

Technical Differences

Side-by-Side Facts

Indexable
FieldPhi-4-multimodal-instructGrok 4.6
DeveloperMicrosoftxAI
FamilyPhi 4 Multimodal InstructGrok 4
ModelPhi-4-multimodal-instructGrok 4.6
VersionPhi-4-multimodal-instructGrok 4.6
Lifecycleactiveactive
Released2025-02-26Unknown
Knowledge cutoffUnknown2026-02-01
Input modalitiesText, Image, AudioText, Image
Output modalitiesTextText
Context window131K500K
Total parameters5.6BUnknown
Active parametersUnknownUnknown
LicensemitUnknown
Open weightsYesNo
API availableUnknownYes
Self-hostableYesNo
Provider accessUnknownXai (Standard)
Capabilitieschat, generationchat, generation, reasoning, tools

11 comparable fields · 9 material differences · Pair passes the primary-source comparison gate

Phi-4 Multimodal Instruct Capabilities

chatgeneration
Input price
Output price
Serving providers0
Canonical IDmicrosoft/Phi-4-multimodal-instruct

Grok 4.6 Capabilities

chatgenerationreasoningtools
Input price$2.00
Output price$6.00
Serving providers1
Canonical IDxai/grok-4.6

Internal Comparison Graph

Related Comparisons

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Primary Evidence

Sources and Freshness

Questions

Phi-4 Multimodal Instruct vs Grok 4.6 FAQs

Is Phi-4 Multimodal Instruct or Grok 4.6 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Phi-4 Multimodal Instruct and Grok 4.6, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Phi-4 Multimodal Instruct or Grok 4.6?+

Only Grok 4.6 has a directly sourced input price: $2.00 per million tokens. Only Grok 4.6 has a directly sourced output price: $6.00 per million tokens.

Which has a larger context window, Phi-4 Multimodal Instruct or Grok 4.6?+

Grok 4.6 has the larger sourced context window. Phi-4 Multimodal Instruct supports 131K and Grok 4.6 supports 500K.

Which performs better in benchmarks, Phi-4 Multimodal Instruct or Grok 4.6?+

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

Can Phi-4 Multimodal Instruct or Grok 4.6 be self-hosted?+

Phi-4 Multimodal Instruct is the only model in this pair currently marked as self-hostable. Phi-4 Multimodal Instruct is open weight; Grok 4.6 is not marked open weight.

Can Phi-4 Multimodal Instruct and Grok 4.6 understand images?+

Phi-4 Multimodal Instruct is documented with image input; Grok 4.6 is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Phi-4 Multimodal Instruct or Grok 4.6?+

Neither has a larger sourced maximum output. Phi-4 Multimodal Instruct is — and Grok 4.6 is —.

Do Phi-4 Multimodal Instruct and Grok 4.6 support reasoning and tool use?+

Phi-4 Multimodal Instruct: image input. Grok 4.6: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Phi-4 Multimodal Instruct or Grok 4.6?+

Phi-4 Multimodal Instruct has 0 sourced provider routes; Grok 4.6 has 1, so Grok 4.6 has broader tracked availability.

Which offers better value, Phi-4 Multimodal Instruct or Grok 4.6?+

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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