Ember-1 vs Qwen3 VL 30B A3B Thinking
Qwen3 VL 30B A3B Thinking costs 15.0x less per output token than Ember-1 ($1.00 vs $15.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- 52.6
- Overall
- No data
- Output $/M
- $15.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.00
Ember-1 or Qwen3 VL 30B A3B Thinking: which to pick
Only Ember-1 has a coding score, 52.6 on the Vibe Coding Index; Qwen3 VL 30B A3B Thinking has none, so the two cannot be ranked on coding.
Pick Qwen3 VL 30B A3B Thinking for output tokens 15.0x cheaper ($1.00 vs $15.00 per million).
No benchmark has tested both yet. Ember-1 has results on Terminal-Bench 4 (Vals AI), Vibe Code Bench (Vals AI) and Code migration (Vals AI); Qwen3 VL 30B A3B Thinking on AA Intelligence Index. 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
Only Ember-1 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Qwen3 VL 30B A3B Thinking has a AA Intelligence Index result, 9.5.
Directional only
Long documents
Listed context window
Ember-1
Ember-1 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 VL 30B A3B Thinking
Ember-1 $0.011, Qwen3 VL 30B A3B Thinking $0.0008 per turn.
List prices
At a glance
- Coding index
- Ember-1 52.6 from 2 benchmarks, Qwen3 VL 30B A3B Thinking 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
- Ember-1 $15.00 against Qwen3 VL 30B A3B Thinking $1.00 per million output tokens, 15.0x apart.
- Context window
- Ember-1 takes 1.05M tokens, Qwen3 VL 30B A3B Thinking 262K.
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 Index5 boards measured
| Benchmark | Ember-1 | Qwen3 VL 30B A3B Thinking | Leader |
|---|---|---|---|
| Terminal-Bench 4 (Vals AI) | 20.7% | Not measured | Only Ember-1 measured |
| Vibe Code Bench (Vals AI) | 83.9% | Not measured | Only Ember-1 measured |
| Code migration (Vals AI) | 32.5% | Not measured | Only Ember-1 measured |
| IOI (Vals AI) | 46.3% | Not measured | Only Ember-1 measured |
| CyberBench (Vals AI) | 69.5% | Not measured | Only Ember-1 measured |
| Neither model has a result on the other 38 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Ember-1 | Qwen3 VL 30B A3B Thinking | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 9.5 | Only Qwen3 VL 30B A3B Thinking measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Ember-1 | Qwen3 VL 30B A3B Thinking | Leader |
|---|---|---|---|
| Finance Agent (Vals AI) | 51.8% | Not measured | Only Ember-1 measured |
| Tax Agent Bench (Vals AI) | 31.1% | Not measured | Only Ember-1 measured |
| Legal Research Bench (Vals AI) | 44.7% | Not measured | Only Ember-1 measured |
| Excel Modeling Benchmark (Vals AI) | 63.4% | Not measured | Only Ember-1 measured |
| BioMysteryBench (Vals AI) | 67.0% | Not measured | Only Ember-1 measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | Not measured | Only Ember-1 measured |
| Vals Science Index | 31.8% | Not measured | Only Ember-1 measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Ember-1 | Qwen3 VL 30B A3B Thinking | Leader |
|---|---|---|---|
| MysteryMechanism (Vals AI) | 22.5% | Not measured | Only Ember-1 measured |
| Neither model has a result on the other 22 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Ember-1 | Qwen3 VL 30B A3B Thinking | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 66.2% | Not measured | Only Ember-1 measured |
| Neither model has a result on the other 47 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
Qwen3 VL 30B A3B Thinking costs less
Repository review
50K input + 3K output tokens
Qwen3 VL 30B A3B Thinking costs less
Agent loop
200K input + 10K output tokens
Qwen3 VL 30B A3B Thinking 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 | Fireworks Ember-1 | Qwen3 VL 30B A3B Thinking |
|---|---|---|
| Maker | Fireworks | Qwen |
| Weights | No public weights listed | Open weights |
| Released | September 24, 2026 | October 6, 2025 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $3.00 | $0.29 |
| Output $/Mtok | $15.00 | $1.00 |
| Coding index | 52.6 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ember-1 better than Qwen3 VL 30B A3B Thinking for coding?
Only Ember-1 has a coding score, 52.6 on the Vibe Coding Index; Qwen3 VL 30B A3B Thinking has none, so the two cannot be ranked on coding. Pick Qwen3 VL 30B A3B Thinking for output tokens 15.0x cheaper ($1.00 vs $15.00 per million).
Which is cheaper, Ember-1 or Qwen3 VL 30B A3B Thinking?
Ember-1 costs $3.00 per million input tokens and $15.00 per million output tokens; Qwen3 VL 30B A3B Thinking costs $0.29 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Ember-1 or Qwen3 VL 30B A3B Thinking?
Ember-1, with 1.05M tokens against 262K.
Has any benchmark tested both Ember-1 and Qwen3 VL 30B A3B Thinking?
No benchmark has tested both yet. Ember-1 has results on Terminal-Bench 4 (Vals AI), Vibe Code Bench (Vals AI) and Code migration (Vals AI); Qwen3 VL 30B A3B Thinking on AA Intelligence Index. Compare them on price and context instead. Data as of October 22, 2026.