phi-4 vs GLM 5.3 Flash
At a Glance
| Compare |  phi-4Microsoft |  GLM 5.3 FlashZ.ai |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #29 of 4654.6 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 36.4–69.8 |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #2 of 44$0.0087 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #1 of 3877.3 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 68.2–84.9 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.070Deepinfra ↗ · Sep 22, 2026 | $0.075Z.ai ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | $0.14Deepinfra ↗ · Sep 22, 2026 | $0.25Z.ai ↗ · Aug 29, 2026 |
| Context windowMaximum documented tokens | 16K | 1,000K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 2, 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
| Benchmark | phi-4 | GLM-5.3-Flash |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,216.6083% of row best · rating · phi-4; 95% CI [1212.02298793, 1221.18318193]; votes 24126; rank 300 | 1,471.89100% of row best · rating · glm-5.3-flash; 95% CI [1465.37026588, 1478.41920488]; votes 10038; rank 24 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 1 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
| Field | phi-4 | GLM-5.3-Flash |
|---|---|---|
| Developer | Microsoft | Z.ai |
| Family | Phi 4 | Glm 5 3 Flash |
| Model | phi-4 | GLM-5.3-Flash |
| Version | phi-4 | GLM-5.3-Flash |
| Lifecycle | active | active |
| Released | 2024-12-12 | 2026-09-02 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image, Video, Document |
| Output modalities | Text | Text |
| Context window | 16K | 1,000K |
| Total parameters | 14.7B | 320B |
| Active parameters | Unknown | 18B |
| License | mit | MIT |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard) |
| Capabilities | chat, generation | agents, chat, computer-use, reasoning, structured_outputs, tools, vision |
phi-4 Capabilities
GLM 5.3 Flash Capabilities
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Primary Evidence
Sources and Freshness
Questions
phi-4 vs GLM 5.3 Flash FAQs
Is phi-4 or GLM 5.3 Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both phi-4 and GLM 5.3 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, phi-4 or GLM 5.3 Flash?+
phi-4 is $0.070 and GLM 5.3 Flash is $0.075 per million tokens, so phi-4 is cheaper on this metric. phi-4 is $0.14 and GLM 5.3 Flash is $0.25 per million tokens, so phi-4 is cheaper on this metric.
Which has a larger context window, phi-4 or GLM 5.3 Flash?+
GLM 5.3 Flash has the larger sourced context window. phi-4 supports 16K and GLM 5.3 Flash supports 1,000K.
Which performs better in benchmarks, phi-4 or GLM 5.3 Flash?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can phi-4 or GLM 5.3 Flash be self-hosted?+
Both models have the same recorded self-hosting status: supported. phi-4 is open weight; GLM 5.3 Flash is open weight.
Can phi-4 and GLM 5.3 Flash understand images?+
phi-4 is not documented with image input; GLM 5.3 Flash is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, phi-4 or GLM 5.3 Flash?+
Neither has a larger sourced maximum output. phi-4 is — and GLM 5.3 Flash is 131K.
Do phi-4 and GLM 5.3 Flash support reasoning and tool use?+
phi-4: none of these features are definitively sourced. GLM 5.3 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, phi-4 or GLM 5.3 Flash?+
phi-4 has 3 sourced provider routes; GLM 5.3 Flash has 4, so GLM 5.3 Flash has broader tracked availability.
Which offers better value, phi-4 or GLM 5.3 Flash?+
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.