Ember-1 vs GPT-5 Nano
GPT-5 Nano costs 37.5x less per output token than Ember-1 ($0.40 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
- 35.6
- Output $/M
- $0.40
Ember-1 or GPT-5 Nano: which to pick
Only Ember-1 has a coding score, 52.6 on the Vibe Coding Index; GPT-5 Nano has none, so the two cannot be ranked on coding.
Pick GPT-5 Nano for output tokens 37.5x cheaper ($0.40 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); GPT-5 Nano on SWE-bench Verified, LiveCodeBench (Vals AI) and LiveCodeBench (Artificial Analysis 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
Only Ember-1 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-5 Nano has a AA Intelligence Index result, 13.0.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5 Nano has a GPQA Diamond result, 63.4%.
Directional only
Math
AIME
No call
Only GPT-5 Nano has a AIME result, 81.2%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5 Nano has a MMLU Pro result, 76.1%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5 Nano has a Design Arena: websites result, 1101.
Directional only
Long documents
Listed context window
Ember-1
Ember-1 takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5 Nano
Ember-1 $0.011, GPT-5 Nano $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5 Nano has the number, $0.109.
Directional only
At a glance
- Coding index
- Ember-1 52.6 from 2 benchmarks, GPT-5 Nano 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 GPT-5 Nano $0.40 per million output tokens, 37.5x apart.
- Context window
- Ember-1 takes 1.05M tokens, GPT-5 Nano 400K.
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 Index13 boards measured
| Benchmark | Ember-1 | GPT-5 Nano | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 34.8% | Only GPT-5 Nano measured |
| LiveCodeBench (Vals AI) | Not measured | 70.2% | Only GPT-5 Nano measured |
| 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 |
| LiveCodeBench (Artificial Analysis run) | Not measured | 78.9% | Only GPT-5 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 17.4% | Only GPT-5 Nano measured |
| Terminal-Bench | Not measured | 21.8% | Only GPT-5 Nano measured |
| WeirdML | Not measured | 38.1% | Only GPT-5 Nano measured |
| LMArena Text: coding | Not measured | 1351 | Only GPT-5 Nano measured |
| LMArena Text: software and IT | Not measured | 1345 | Only GPT-5 Nano measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Ember-1 | GPT-5 Nano | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 13.0 | Only GPT-5 Nano measured |
| Epoch Capabilities Index | Not measured | 139.2 | Only GPT-5 Nano measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | Ember-1 | GPT-5 Nano | 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 |
| τ²-Bench Telecom | Not measured | 36.5% | Only GPT-5 Nano measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 51.4% | Only GPT-5 Nano measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index17 boards measured
| Benchmark | Ember-1 | GPT-5 Nano | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 63.4% | Only GPT-5 Nano measured |
| MysteryMechanism (Vals AI) | 22.5% | Not measured | Only Ember-1 measured |
| MMMU Pro (Vals AI) | Not measured | 70.9% | Only GPT-5 Nano measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 67.6% | Only GPT-5 Nano measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 9.5% | Only GPT-5 Nano measured |
| GPQA Diamond (Epoch AI run) | Not measured | 69.4% | Only GPT-5 Nano measured |
| ARC-AGI | Not measured | 20.7% | Only GPT-5 Nano measured |
| ARC-AGI-2 | Not measured | 2.6% | Only GPT-5 Nano measured |
| Chess puzzles | Not measured | 22.0% | Only GPT-5 Nano measured |
| Mystery game puzzles | Not measured | 9.0% | Only GPT-5 Nano measured |
| VPCT | Not measured | 37.2% | Only GPT-5 Nano measured |
| LMArena Text: hard prompts | Not measured | 1328 | Only GPT-5 Nano measured |
| LMArena Text: expert | Not measured | 1321 | Only GPT-5 Nano measured |
| LMArena Text: hard prompts in English | Not measured | 1338 | Only GPT-5 Nano measured |
| LMArena Vision: diagrams | Not measured | 1141 | Only GPT-5 Nano measured |
| LMArena Vision: homework | Not measured | 1157 | Only GPT-5 Nano measured |
| Kagi LLM Benchmark | Not measured | 62.2% | Only GPT-5 Nano measured |
| Neither model has a result on the other 5 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index12 boards measured
| Benchmark | Ember-1 | GPT-5 Nano | Leader |
|---|---|---|---|
| AIME | Not measured | 81.2% | Only GPT-5 Nano measured |
| MATH 500 (Vals AI) | Not measured | 93.8% | Only GPT-5 Nano measured |
| MGSM (Vals AI) | Not measured | 89.3% | Only GPT-5 Nano measured |
| AA Math Index | Not measured | 83.7 | Only GPT-5 Nano measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 83.7% | Only GPT-5 Nano measured |
| OTIS Mock AIME | Not measured | 81.1% | Only GPT-5 Nano measured |
| FrontierMath, tiers 1 to 3 | Not measured | 20.0% | Only GPT-5 Nano measured |
| FrontierMath, tier 4 | Not measured | 2.4% | Only GPT-5 Nano measured |
| ProofBench | Not measured | 12.0% | Only GPT-5 Nano measured |
| MATH level 5 | Not measured | 95.2% | Only GPT-5 Nano measured |
| LMArena Text: math | Not measured | 1317 | Only GPT-5 Nano measured |
| LMArena Text: mathematical work | Not measured | 1326 | Only GPT-5 Nano measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards measured
| Benchmark | Ember-1 | GPT-5 Nano | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 76.1% | Only GPT-5 Nano measured |
| LegalBench (Vals AI) | Not measured | 50.1% | Only GPT-5 Nano measured |
| CaseLaw (Vals AI) | Not measured | 52.6% | Only GPT-5 Nano measured |
| TaxEval (Vals AI) | Not measured | 67.4% | Only GPT-5 Nano measured |
| MortgageTax (Vals AI) | Not measured | 53.6% | Only GPT-5 Nano measured |
| MedQA (Vals AI) | Not measured | 93.3% | Only GPT-5 Nano measured |
| MedCode (Vals AI) | Not measured | 30.4% | Only GPT-5 Nano measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 78.0% | Only GPT-5 Nano measured |
| SimpleQA Verified | Not measured | 11.7% | Only GPT-5 Nano measured |
| LMArena Text: science | Not measured | 1318 | Only GPT-5 Nano measured |
| LMArena Text: medicine and healthcare | Not measured | 1335 | Only GPT-5 Nano measured |
| LMArena Text: legal and government | Not measured | 1298 | Only GPT-5 Nano measured |
| LMArena Text: business and finance | Not measured | 1311 | Only GPT-5 Nano measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Ember-1 | GPT-5 Nano | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1101 | Only GPT-5 Nano measured |
| Design Arena: UI components | Not measured | 1064 | Only GPT-5 Nano measured |
| Design Arena: game dev | Not measured | 1044 | Only GPT-5 Nano measured |
| Design Arena: data viz | Not measured | 1056 | Only GPT-5 Nano measured |
| Design Arena: 3D | Not measured | 965 | Only GPT-5 Nano measured |
| Design Arena: all code categories | Not measured | 1084 | Only GPT-5 Nano measured |
| Neither model has a result on the other 3 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index29 boards measured
| Benchmark | Ember-1 | GPT-5 Nano | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 66.2% | Not measured | Only Ember-1 measured |
| SAGE (Vals AI) | Not measured | 30.4% | Only GPT-5 Nano measured |
| MedScribe (Vals AI) | Not measured | 72.9% | Only GPT-5 Nano measured |
| IFBench | Not measured | 67.6% | Only GPT-5 Nano measured |
| Long context reasoning (AA-LCR) | Not measured | 45.0% | Only GPT-5 Nano measured |
| DTBench | Not measured | 62.7% | Only GPT-5 Nano measured |
| LMCA | Not measured | 7.9% | Only GPT-5 Nano measured |
| Fiction.LiveBench | Not measured | 44.4% | Only GPT-5 Nano measured |
| LMArena Text | Not measured | 1320 | Only GPT-5 Nano measured |
| LMArena Text: instruction following | Not measured | 1306 | Only GPT-5 Nano measured |
| LMArena Text: creative writing | Not measured | 1249 | Only GPT-5 Nano measured |
| LMArena Vision | Not measured | 1159 | Only GPT-5 Nano measured |
| LMArena Text: English | Not measured | 1321 | Only GPT-5 Nano measured |
| LMArena Text: non-English | Not measured | 1313 | Only GPT-5 Nano measured |
| LMArena Text: Chinese | Not measured | 1356 | Only GPT-5 Nano measured |
| LMArena Text: German | Not measured | 1327 | Only GPT-5 Nano measured |
| LMArena Text: Japanese | Not measured | 1227 | Only GPT-5 Nano measured |
| LMArena Text: Korean | Not measured | 1269 | Only GPT-5 Nano measured |
| LMArena Text: Spanish | Not measured | 1360 | Only GPT-5 Nano measured |
| LMArena Text: Russian | Not measured | 1296 | Only GPT-5 Nano measured |
| LMArena Text: Polish | Not measured | 1314 | Only GPT-5 Nano measured |
| LMArena Text: multi-turn | Not measured | 1311 | Only GPT-5 Nano measured |
| LMArena Text: longer queries | Not measured | 1312 | Only GPT-5 Nano measured |
| LMArena Text: writing and language | Not measured | 1283 | Only GPT-5 Nano measured |
| LMArena Text: entertainment and media | Not measured | 1268 | Only GPT-5 Nano measured |
| LMArena Vision: English | Not measured | 1170 | Only GPT-5 Nano measured |
| LMArena Vision: Chinese | Not measured | 1176 | Only GPT-5 Nano measured |
| LMArena Vision: reading text | Not measured | 1152 | Only GPT-5 Nano measured |
| LMArena Vision: humor | Not measured | 1110 | Only GPT-5 Nano measured |
| Neither model has a result on the other 17 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
GPT-5 Nano costs less
Repository review
50K input + 3K output tokens
GPT-5 Nano costs less
Agent loop
200K input + 10K output tokens
GPT-5 Nano 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 | OpenAI GPT-5 Nano |
|---|---|---|
| Maker | Fireworks | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | September 24, 2026 | August 7, 2025 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $3.00 | $0.05 |
| Output $/Mtok | $15.00 | $0.40 |
| Coding index | 52.6 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | Not computable | $0.109 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ember-1 better than GPT-5 Nano for coding?
Only Ember-1 has a coding score, 52.6 on the Vibe Coding Index; GPT-5 Nano has none, so the two cannot be ranked on coding. Pick GPT-5 Nano for output tokens 37.5x cheaper ($0.40 vs $15.00 per million).
Which is cheaper, Ember-1 or GPT-5 Nano?
Ember-1 costs $3.00 per million input tokens and $15.00 per million output tokens; GPT-5 Nano costs $0.05 and $0.40. Cost per solved task is known for GPT-5 Nano only.
Which has the bigger context window, Ember-1 or GPT-5 Nano?
Ember-1, with 1.05M tokens against 400K.
Has any benchmark tested both Ember-1 and GPT-5 Nano?
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); GPT-5 Nano on SWE-bench Verified, LiveCodeBench (Vals AI) and LiveCodeBench (Artificial Analysis run). Compare them on price and context instead. Data as of October 22, 2026.