Nova Premier 1.0 vs Qwen2.5 7B Instruct
Qwen2.5 7B Instruct costs 62.5x less per output token than Nova Premier 1.0 ($0.20 vs $12.50 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $12.50
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.20
Nova Premier 1.0 or Qwen2.5 7B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nova Premier 1.0 for a larger context window (1M against 33K tokens).
No benchmark has tested both yet. Nova Premier 1.0 has results on LiveCodeBench (Artificial Analysis run), Terminal-Bench Hard (Artificial Analysis run) and ALE-Bench; Qwen2.5 7B Instruct on Epoch Capabilities Index, BALROG and GPQA Diamond (Epoch AI run). Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Nova Premier 1.0 has a AA Intelligence Index result, 9.2.
Directional only
Web design
Design Arena: websites
No call
Only Nova Premier 1.0 has a Design Arena: websites result, 835.
Directional only
Long documents
Listed context window
Nova Premier 1.0
Nova Premier 1.0 takes 1M tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 7B Instruct
Nova Premier 1.0 $0.0088, Qwen2.5 7B Instruct $0.0002 per turn.
List prices
At a glance
- Coding index
- Nova Premier 1.0 not benchmarked, Qwen2.5 7B Instruct not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Nova Premier 1.0 $12.50 against Qwen2.5 7B Instruct $0.20 per million output tokens, 62.5x apart.
- Context window
- Nova Premier 1.0 takes 1M tokens, Qwen2.5 7B Instruct 33K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards measured
| Benchmark | Nova Premier 1.0 | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 31.7% | Not measured | Only Nova Premier 1.0 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.8% | Not measured | Only Nova Premier 1.0 measured |
| ALE-Bench | 147.4 | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Nova Premier 1.0 | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | Not measured | Only Nova Premier 1.0 measured |
| Epoch Capabilities Index | Not measured | 118.5 | Only Qwen2.5 7B Instruct measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Nova Premier 1.0 | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 38.3% | Not measured | Only Nova Premier 1.0 measured |
| BALROG | Not measured | 7.8% | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Nova Premier 1.0 | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 56.9% | Not measured | Only Nova Premier 1.0 measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | Not measured | Only Nova Premier 1.0 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 35.5% | Only Qwen2.5 7B Instruct measured |
| Kagi LLM Benchmark | 44.8% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Nova Premier 1.0 | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| AA Math Index | 17.3 | Not measured | Only Nova Premier 1.0 measured |
| AIME 2025 (Artificial Analysis run) | 17.3% | Not measured | Only Nova Premier 1.0 measured |
| OTIS Mock AIME | Not measured | 2.5% | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Nova Premier 1.0 | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 73.3% | Not measured | Only Nova Premier 1.0 measured |
| MMLU | Not measured | 72.9% | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 16 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Nova Premier 1.0 | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 835 | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 8 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Nova Premier 1.0 | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| IFBench | 36.2% | Not measured | Only Nova Premier 1.0 measured |
| Long context reasoning (AA-LCR) | 34.3% | Not measured | Only Nova Premier 1.0 measured |
| DTBench | Not measured | 47.7% | Only Qwen2.5 7B Instruct measured |
| LMCA | Not measured | 6.4% | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 42 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Qwen2.5 7B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 7B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 7B Instruct costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Amazon Nova Premier 1.0 | Qwen2.5 7B Instruct |
|---|---|---|
| Maker | Amazon | Qwen |
| Weights | No public weights listed | Open weights |
| Released | October 31, 2025 | October 16, 2024 |
| Context window | 1M | 33K |
| Input $/Mtok | $2.50 | $0.10 |
| Output $/Mtok | $12.50 | $0.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Nova Premier 1.0 better than Qwen2.5 7B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Premier 1.0 for a larger context window (1M against 33K tokens).
Which is cheaper, Nova Premier 1.0 or Qwen2.5 7B Instruct?
Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 per million output tokens; Qwen2.5 7B Instruct costs $0.10 and $0.20. Cost per solved task is known for neither of them.
Which has the bigger context window, Nova Premier 1.0 or Qwen2.5 7B Instruct?
Nova Premier 1.0, with 1M tokens against 33K.
Has any benchmark tested both Nova Premier 1.0 and Qwen2.5 7B Instruct?
No benchmark has tested both yet. Nova Premier 1.0 has results on LiveCodeBench (Artificial Analysis run), Terminal-Bench Hard (Artificial Analysis run) and ALE-Bench; Qwen2.5 7B Instruct on Epoch Capabilities Index, BALROG and GPQA Diamond (Epoch AI run). Compare them on price and context instead. Data as of October 21, 2026.