Phi-4-mini vs Qwen3-Coder 480B-A35B Instruct vs Nova Lite
Nova Lite comes out ahead, 77 to 58 and 28 on our weighted score, and it is the cheaper option too.
MicrosoftPhi-4-mini
58/100- ECI—
- Price$0.075 / $0.30
- Context128K
Alibaba (Qwen)Qwen3-Coder 480B-A35B Instruct
28/100- ECI—
- Price$1.50 / $7.50
- Context262K
- Our pick
AmazonNova Lite
77/100- ECI—
- Price$0.06 / $0.24
- Context300K
Nova Lite is our pick
Nova Lite is the better all-round choice, scoring 77/100 against Phi-4-mini (58) and Qwen3-Coder 480B-A35B Instruct (28). It leads on price, inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceNova LiteNova Lite $0.105 · Phi-4-mini $0.131 · Qwen3-Coder 480B-A35B Instruct $3.00 per 1M tokens (3:1 blend)
- Longest contextNova LiteNova Lite 300,000 · Qwen3-Coder 480B-A35B Instruct 262,144 · Phi-4-mini 128,000 tokens
- Widest inputsNova LitePhi-4-mini: Text · Qwen3-Coder 480B-A35B Instruct: Text · Nova Lite: Text, Images, PDFs, Video
- Self-hostingPhi-4-mini and Qwen3-Coder 480B-A35B InstructPublishes downloadable weights
| Measure | Weight | Phi-4-mini | Qwen3-Coder 480B-A35B Instruct | Nova Lite |
|---|---|---|---|---|
| Price | 50% | 92 | 27 | 96 |
| Inputs & features | 30% | 25 | 25 | 70 |
| Context window | 20% | 24 | 37 | 39 |
| Overall | 100% | 58/100 | 28/100 | 77/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Phi-4-miniMicrosoft | Qwen3-Coder 480B-A35B InstructAlibaba (Qwen) | Nova LiteAmazon |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.075 | $1.50 | $0.06 (best) |
| Output | $0.30 | $7.50 | $0.24 (best) |
| Cached input | — | — | $0.015 |
| Blended (3:1) | $0.131 | $3.00 | $0.105 (best) |
| Long-context rate | Same rate | Over 32K: $2.70 / $13.50 | Same rate |
| Price source | Official Azure API | Official Alibaba API | Official Amazon Bedrock API |
| Limits | |||
| Context window | 128,000 tokens | 262,144 tokens | 300,000 tokens (best) |
| Max output | 4,096 tokens | 65,536 tokens (best) | 10,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | phi-4-mini | qwen3-coder-480b-a35b-instruct | amazon.nova-lite-v1:0 |
| API providers | 1 | 7 (best) | 3 |
| Released | Dec 11, 2024 | Apr 2025 | Dec 3, 2024 |
| Knowledge cutoff | Oct 2023 | Apr 2025 | Oct 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Phi-4-mini$1.35
- Qwen3-Coder 480B-A35B Instruct$30.00
- Nova Lite$1.08
Which should you choose?
Which is better: Phi-4-mini, Qwen3-Coder 480B-A35B Instruct or Nova Lite?
Nova Lite is the better all-round choice, scoring 77/100 against Phi-4-mini (58) and Qwen3-Coder 480B-A35B Instruct (28). It leads on price, inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Phi-4-mini, Qwen3-Coder 480B-A35B Instruct or Nova Lite?
Nova Lite is cheaper at $0.06 input / $0.24 output per million tokens (official Amazon Bedrock API price). Phi-4-mini costs $0.075 input / $0.30 output per million tokens (official Azure API price); Qwen3-Coder 480B-A35B Instruct costs $1.50 input / $7.50 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.105 per million tokens for Nova Lite versus $0.131 for Phi-4-mini (1.2× as much) and $3.00 for Qwen3-Coder 480B-A35B Instruct (29× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Phi-4-mini has not been scored yet, Qwen3-Coder 480B-A35B Instruct has not been scored yet and Nova Lite has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Phi-4-mini, Qwen3-Coder 480B-A35B Instruct and Nova Lite yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Nova Lite has the largest context window at 300,000 tokens, against 262,144 for Qwen3-Coder 480B-A35B Instruct and 128,000 for Phi-4-mini. Maximum output per response: Phi-4-mini up to 4,096, Qwen3-Coder 480B-A35B Instruct up to 65,536, Nova Lite up to 10,000 tokens.
Which can read images, PDFs, audio or video?
Phi-4-mini accepts text; Qwen3-Coder 480B-A35B Instruct accepts text; Nova Lite accepts text, images, PDFs and video. Nova Lite handles the widest range of inputs.
Are any of these open source?
Phi-4-mini and Qwen3-Coder 480B-A35B Instruct publishes its weights and can be self-hosted; Nova Lite is proprietary.
Which is newer?
Qwen3-Coder 480B-A35B Instruct is the newest, released Apr 2025. Phi-4-mini came out Dec 11, 2024; Nova Lite came out Dec 3, 2024. Knowledge cutoff: Phi-4-mini Oct 2023, Qwen3-Coder 480B-A35B Instruct Apr 2025, Nova Lite Oct 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
