Nova Lite vs Llama-3.1-8B-Instruct vs Phi-4-mini
Nova Lite comes out ahead, 77 to 58 and 56 on our weighted score, and it is the cheaper option too.
- Our pick
AmazonNova Lite
77/100- ECI—
- Price$0.06 / $0.24
- Context300K
MetaLlama-3.1-8B-Instruct
56/100- ECI116.6
- Price$0.152 / $0.167
- Context128K
MicrosoftPhi-4-mini
58/100- ECI—
- Price$0.075 / $0.30
- Context128K
Nova Lite is our pick
Nova Lite is the better all-round choice, scoring 77/100 against Phi-4-mini (58) and Llama-3.1-8B-Instruct (56). 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 · Llama-3.1-8B-Instruct $0.156 per 1M tokens (3:1 blend)
- Longest contextNova LiteNova Lite 300,000 · Llama-3.1-8B-Instruct 128,000 · Phi-4-mini 128,000 tokens
- Widest inputsNova LiteNova Lite: Text, Images, PDFs, Video · Llama-3.1-8B-Instruct: Text · Phi-4-mini: Text
- Self-hostingLlama-3.1-8B-Instruct and Phi-4-miniPublishes downloadable weights
| Measure | Weight | Nova Lite | Llama-3.1-8B-Instruct | Phi-4-mini |
|---|---|---|---|---|
| Price | 50% | 96 | 88 | 92 |
| Inputs & features | 30% | 70 | 25 | 25 |
| Context window | 20% | 39 | 24 | 24 |
| Overall | 100% | 77/100 | 56/100 | 58/100 |
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 | Nova LiteAmazon | Llama-3.1-8B-InstructMeta | Phi-4-miniMicrosoft |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 116.6 | — |
| ECI rank | — | #145 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 27.0% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 1.7% | — |
| Price per million tokens | |||
| Input | $0.06 (best) | $0.152 | $0.075 |
| Output | $0.24 | $0.167 (best) | $0.30 |
| Cached input | $0.015 | — | — |
| Blended (3:1) | $0.105 (best) | $0.156 | $0.131 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Amazon Bedrock API | Median of 9 providers | Official Azure API |
| Limits | |||
| Context window | 300,000 tokens (best) | 128,000 tokens | 128,000 tokens |
| Max output | 10,000 tokens (best) | 4,096 tokens | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | amazon.nova-lite-v1:0 | — | phi-4-mini |
| API providers | 3 | 9 (best) | 1 |
| Released | Dec 3, 2024 | Jul 23, 2024 | Dec 11, 2024 |
| Knowledge cutoff | Oct 2024 | Dec 2023 | Oct 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Nova Lite$1.08
- Llama-3.1-8B-Instruct$1.85
- Phi-4-mini$1.35
Which should you choose?
Which is better: Nova Lite, Llama-3.1-8B-Instruct or Phi-4-mini?
Nova Lite is the better all-round choice, scoring 77/100 against Phi-4-mini (58) and Llama-3.1-8B-Instruct (56). 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, Nova Lite, Llama-3.1-8B-Instruct or Phi-4-mini?
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); Llama-3.1-8B-Instruct costs $0.152 input / $0.167 output per million tokens (median across 9 API providers). 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 $0.156 for Llama-3.1-8B-Instruct (1.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Nova Lite has not been scored yet, Llama-3.1-8B-Instruct has an ECI of 116.6 and Phi-4-mini has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Nova Lite, Llama-3.1-8B-Instruct and Phi-4-mini 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 128,000 for Llama-3.1-8B-Instruct and 128,000 for Phi-4-mini. Maximum output per response: Nova Lite up to 10,000, Llama-3.1-8B-Instruct up to 4,096, Phi-4-mini up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Nova Lite accepts text, images, PDFs and video; Llama-3.1-8B-Instruct accepts text; Phi-4-mini accepts text. Nova Lite handles the widest range of inputs.
Are any of these open source?
Llama-3.1-8B-Instruct and Phi-4-mini publishes its weights and can be self-hosted; Nova Lite is proprietary.
Which is newer?
Phi-4-mini is the newest, released Dec 11, 2024. Nova Lite came out Dec 3, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Nova Lite Oct 2024, Llama-3.1-8B-Instruct Dec 2023, Phi-4-mini Oct 2023.
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.
