API cost decision in 10 seconds

NewEmber-1 vs NewQwen3.8 Max Prime

Pick Qwen3.8 Max Prime for lower cost; pick Ember-1 only if the larger context window matters more.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Qwen3.8 Max Prime for lower cost; pick Ember-1 only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Qwen3.8 Max Prime is estimated at $10 vs $10.5 for Ember-1, saving $0.5 (4.8% lower).

Cost-first pickQwen3.8 Max Prime
Context-first pickEmber-1
Sample savings$0.54.8%
10x traffic gap$5

Ember-1 has more context, but Qwen3.8 Max Prime saves $0.5 on the standard workload. At 10x that traffic, the same price gap is about $5. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Cost winner changes by workload shape: input-heavy / RAG favors Ember-1, balanced workload favors Qwen3.8 Max Prime, and output-heavy chatbot favors Qwen3.8 Max Prime.

Workload shapeToken mixBetter pickEmber-1Qwen3.8 Max Prime
Input-heavy / RAG5M input + 500K outputEmber-1$22.5$26
Balanced workload1M input + 1M outputQwen3.8 Max Prime$18$16
Output-heavy chatbot1M input + 5M outputQwen3.8 Max Prime$78$64
Cheaper input Ember-1 $3 vs $4 / 1M

Ember-1 is $1 cheaper per 1M input tokens (25% lower; 1.33x difference).

Cheaper output Qwen3.8 Max Prime $15 vs $12 / 1M

Qwen3.8 Max Prime is $3 cheaper per 1M output tokens (20% lower; 1.25x difference).

Larger context Ember-1 1.05M vs 1M

Ember-1 has 48.58K more context (1.05x larger).

Sample workload Qwen3.8 Max Prime $10.5 vs $10

Qwen3.8 Max Prime is $0.5 cheaper on the standard workload (4.8% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Ember-1 Calculating… Estimated API cost
Qwen3.8 Max Prime Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Ember-1 has the lower input price; Qwen3.8 Max Prime has the lower output price; Ember-1 offers the larger context window. For the 1M input plus 500K output sample, Qwen3.8 Max Prime is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $10.5 for Ember-1 and $10 for Qwen3.8 Max Prime.

Best Fit

Choose Ember-1 when you care most about lower input-token price, and larger context window.

Choose Qwen3.8 Max Prime when you care most about lower output-token price.

Decision Notes
  • On the standard 1M input plus 500K output workload, Qwen3.8 Max Prime is estimated at $10 vs $10.5 for Ember-1, saving $0.5 (4.8% lower).
  • Qwen3.8 Max Prime is $0.5 cheaper on the standard workload (4.8% lower).
  • Ember-1 is $1 cheaper per 1M input tokens (25% lower; 1.33x difference).
  • Qwen3.8 Max Prime is $3 cheaper per 1M output tokens (20% lower; 1.25x difference).
  • Ember-1 has 48.58K more context (1.05x larger).
Head-to-Head Specs
FeatureNewEmber-1
(Fireworks)
NewQwen3.8 Max Prime
(Qwen)
Input Price
prompt tokens per 1M
$3$4
Completion Price
per 1M tokens
$15$12
Sample Workload Cost
1M input + 500K output
$10.5$10
Context Window1.05M1M
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionQwen3.8 Max PrimeOn the standard 1M input plus 500K output workload, Qwen3.8 Max Prime is estimated at $10 vs $10.5 for Ember-1, saving $0.5 (4.8% lower).
High-volume input processingEmber-1Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsQwen3.8 Max PrimeLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workEmber-1A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

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Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

Open largest context models

Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

Open provider hubs

Fireworks catalog

Review all tracked Fireworks models before deciding whether this matchup is the right shortlist.

Open Fireworks models

Qwen catalog

Check other Qwen models with comparable pricing, context, or release timing.

Open Qwen models
Ember-1

Ember-1 is a specialized reasoning model from Fireworks Research, built on [Kimi K3](https://openrouter.ai/moonshotai/kimi-k3). It is designed to make every token go further: it produces shorter reasoning traces, using roughly 40%...

Qwen3.8 Max Prime

Qwen3.8 Max Prime is a higher-throughput variant of Qwen3.8 Max from Alibaba's Qwen team, served as a separate SKU at a higher price point. It accepts text, image, and video...