Ember-1 vs Ling 3.0 Flash
Ember-1 leads Ling 3.0 Flash on coding, 52.6 to 29.6 on the Vibe Coding Index, and Ling 3.0 Flash costs 123.5x less per output token ($0.1215 vs $15.00 per million). Updated October 22, 2026; 6 benchmarks have a result for both.
Ember-1 or Ling 3.0 Flash: which to pick
Pick Ember-1 for coding: it scores 52.6 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash.
Pick Ling 3.0 Flash for output tokens 123.5x cheaper ($0.1215 vs $15.00 per million).
- Shared results
- 6
- Ember-1 only
- 8
- Ling 3.0 Flash only
- 18
- Like-for-like categories
- 3 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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
Ember-1
Ember-1 scores 52.6 against 29.6.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
No call
Only Ling 3.0 Flash has a AA Intelligence Index result, 20.1.
Directional only
Agentic work
AA Agentic Index
No call
Only Ling 3.0 Flash has a AA Agentic Index result, 19.3.
Directional only
Reasoning
GPQA Diamond
No call
Only Ling 3.0 Flash has a GPQA Diamond result, 84.8%.
Directional only
Knowledge
MMLU Pro
No call
Only Ling 3.0 Flash has a MMLU Pro result, 82.0%.
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
Ling 3.0 Flash
Ember-1 $0.011, Ling 3.0 Flash $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Ling 3.0 Flash has the number, $0.05.
Directional only
At a glance
- Coding index
- Ember-1 52.6 from 2 benchmarks, Ling 3.0 Flash 29.6 from 2 benchmarks.
- Widest category
- Coding, 56.7 points apart on average over 2 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Ember-1 83.9% against Ling 3.0 Flash 2.9%, 81.0 points apart on a 0 to 100 scale.
- Output price
- Ember-1 $15.00 against Ling 3.0 Flash $0.1215 per million output tokens, 123.5x apart.
- Context window
- Ember-1 takes 1.05M tokens, Ling 3.0 Flash 262K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Ember-1 | Bars | Ling 3.0 Flash | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Agentic work | 3 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 6 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Ember-1 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 50.6 | Only Ling 3.0 Flash measured |
| LiveCodeBench (Vals AI) | Not measured | 84.0% | Only Ling 3.0 Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 65.2% | Only Ling 3.0 Flash measured |
| Terminal-Bench 4 (Vals AI) | 20.7% | Not measured | Only Ember-1 measured |
| Vibe Code Bench (Vals AI) | 83.9% | 2.9% | Ember-1 |
| Code migration (Vals AI) | 32.5% | 0.0% | Ember-1 |
| IOI (Vals AI) | 46.3% | Not measured | Only Ember-1 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 50.2% | Only Ling 3.0 Flash measured |
| SkillsBench (Vals AI) | Not measured | 27.9% | Only Ling 3.0 Flash measured |
| CyberBench (Vals AI) | 69.5% | Not measured | Only Ember-1 measured |
| SciCode | Not measured | 42.0% | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Ember-1 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 20.1 | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Ember-1 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 19.3 | Only Ling 3.0 Flash measured |
| Finance Agent (Vals AI) | 51.8% | 30.3% | Ember-1 |
| Tax Agent Bench (Vals AI) | 31.1% | Not measured | Only Ember-1 measured |
| Legal Research Bench (Vals AI) | 44.7% | 0.0% | Ember-1 |
| Excel Modeling Benchmark (Vals AI) | 63.4% | 25.0% | Ember-1 |
| 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 33 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Ember-1 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 84.8% | Only Ling 3.0 Flash measured |
| MysteryMechanism (Vals AI) | 22.5% | Not measured | Only Ember-1 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 85.5% | Only Ling 3.0 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 23.7% | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 18 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ember-1 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Ember-1 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 82.0% | Only Ling 3.0 Flash measured |
| LegalBench (Vals AI) | Not measured | 79.7% | Only Ling 3.0 Flash measured |
| CorpFin (Vals AI) | Not measured | 61.9% | Only Ling 3.0 Flash measured |
| TaxEval (Vals AI) | Not measured | 70.7% | Only Ling 3.0 Flash measured |
| MedCode (Vals AI) | Not measured | 32.3% | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 13 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ember-1 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Ember-1 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 66.2% | 50.7% | Ember-1 |
| MedScribe (Vals AI) | Not measured | 80.9% | Only Ling 3.0 Flash measured |
| Long context reasoning (AA-LCR) | Not measured | 73.0% | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ember-1 | Ling 3.0 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 5 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
Ling 3.0 Flash costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash costs less
Agent loop
200K input + 10K output tokens
Ling 3.0 Flash 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 | inclusionAI Ling 3.0 Flash |
|---|---|---|
| Maker | Fireworks | inclusionAI |
| Weights | No public weights listed | Open weights |
| Released | September 24, 2026 | July 23, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $3.00 | $0.0405 |
| Output $/Mtok | $15.00 | $0.1215 |
| Coding index | 52.6 | 29.6 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | $0.05 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ember-1 better than Ling 3.0 Flash for coding?
Pick Ember-1 for coding: it scores 52.6 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash. Pick Ling 3.0 Flash for output tokens 123.5x cheaper ($0.1215 vs $15.00 per million).
Which is cheaper, Ember-1 or Ling 3.0 Flash?
Ember-1 costs $3.00 per million input tokens and $15.00 per million output tokens; Ling 3.0 Flash costs $0.0405 and $0.1215. Cost per solved task is known for Ling 3.0 Flash only.
Which has the bigger context window, Ember-1 or Ling 3.0 Flash?
Ember-1, with 1.05M tokens against 262K.
How many benchmarks is the Ember-1 vs Ling 3.0 Flash comparison based on?
6 benchmarks have a result for both models as of October 22, 2026. Ember-1's coding index rests on 2 independent benchmarks and Ling 3.0 Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.