Qwen3.8 2.4T A95B vs Phi-4 Mini Instruct

At a Glance

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Pricing and Limits
Input priceFrom · USD / 1M tokens$2.00Deepinfra · Sep 22, 2026Not reported
Output priceFrom · USD / 1M tokens$6.00Deepinfra · Sep 22, 2026Not reported
Context windowMaximum documented tokens262K131K
Model facts checkedAug 28, 2026View model evidence →Aug 28, 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 →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldQwen3.8-2.4T-A95BPhi-4-mini-instruct
DeveloperQwenMicrosoft
FamilyQwen3 8 2 4t A95bPhi 4 Mini Instruct
ModelQwen3.8-2.4T-A95BPhi-4-mini-instruct
VersionQwen3.8-2.4T-A95BPhi-4-mini-instruct
Lifecycleactiveactive
ReleasedUnknown2025-02-26
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window262K131K
Total parameters2.4T3.8B
Active parameters95BUnknown
Licenseothermit
Open weightsYesYes
API availableYesYes
Self-hostableYesYes
Provider accessDeepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard)Hugging Face (Standard)
Capabilitieschat, generation, reasoning, toolschat, generation

Qwen3.8 2.4T A95B Capabilities

chatgenerationreasoningtools
Serving providers5
Canonical IDQwen/Qwen3.8-2.4T-A95B

Phi-4 Mini Instruct Capabilities

chatgeneration
Serving providers1
Canonical IDmicrosoft/Phi-4-mini-instruct

Primary Evidence

Sources and Freshness

Questions

Qwen3.8 2.4T A95B vs Phi-4 Mini Instruct FAQs

Is Qwen3.8 2.4T A95B or Phi-4 Mini Instruct better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.8 2.4T A95B and Phi-4 Mini Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Qwen3.8 2.4T A95B or Phi-4 Mini Instruct?+

Only Qwen3.8 2.4T A95B has a directly sourced input price: $2.00 per million tokens. Only Qwen3.8 2.4T A95B has a directly sourced output price: $6.00 per million tokens.

Which has a larger context window, Qwen3.8 2.4T A95B or Phi-4 Mini Instruct?+

Qwen3.8 2.4T A95B has the larger sourced context window. Qwen3.8 2.4T A95B supports 262K and Phi-4 Mini Instruct supports 131K.

Which performs better in benchmarks, Qwen3.8 2.4T A95B or Phi-4 Mini Instruct?+

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

Can Qwen3.8 2.4T A95B or Phi-4 Mini Instruct be self-hosted?+

Both models have the same recorded self-hosting status: supported. Qwen3.8 2.4T A95B is open weight; Phi-4 Mini Instruct is open weight.

Can Qwen3.8 2.4T A95B and Phi-4 Mini Instruct understand images?+

Qwen3.8 2.4T A95B is not documented with image input; Phi-4 Mini Instruct is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Qwen3.8 2.4T A95B or Phi-4 Mini Instruct?+

Neither has a larger sourced maximum output. Qwen3.8 2.4T A95B is — and Phi-4 Mini Instruct is —.

Do Qwen3.8 2.4T A95B and Phi-4 Mini Instruct support reasoning and tool use?+

Qwen3.8 2.4T A95B: reasoning and tool calling. Phi-4 Mini Instruct: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, Qwen3.8 2.4T A95B or Phi-4 Mini Instruct?+

Qwen3.8 2.4T A95B has 5 sourced provider routes; Phi-4 Mini Instruct has 1, so Qwen3.8 2.4T A95B has broader tracked availability.

Which offers better value, Qwen3.8 2.4T A95B or Phi-4 Mini Instruct?+

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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