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steebchen merged 3 commits into from
Nov 8, 2025
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feat: expand canopywave models #1132

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72698ed
feat: expand canopywave models
steebchen Nov 8, 2025
c620243
feat: add changelog
steebchen Nov 8, 2025
daee5d0
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steebchen Nov 8, 2025
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63 changes: 63 additions & 0 deletions apps/ui/src/content/changelog/2025-11-08-canopywave-new-models.md
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@@ -0,0 +1,63 @@
---
id: "13"
slug: "canopywave-new-models"
date: "2025-11-08"
title: "CanopyWave: 3 New Models with 75% Off"
summary: "CanopyWave brings Qwen3 Coder, MiniMax M2, and GLM-4.6 to LLM Gateway with an exclusive 75% discount on all three models."
image:
src: "/changelog/canopywave75.png"
alt: "CanopyWave: 3 New Models with 75% Off"
width: 2046
height: 1102
---

We're excited to announce three new models from **CanopyWave** with an exclusive **75% discount** on all models!

## 🎯 New Models Available

### **GLM-4.6** - Advanced Reasoning

- **Model ID**: `glm-4.6`
- **Provider**: `canopywave/zai/glm-4.6`
- **Context Window**: 202,752 tokens
- **Pricing**: $0.45 per 1M input tokens / $1.50 per 1M output tokens (75% off)
- Enhanced reasoning and tool calling capabilities

### **Qwen3 Coder** - Specialized Coding Model

- **Model ID**: `qwen3-coder`
- **Provider**: `canopywave/qwen/qwen3-coder`
- **Context Window**: 262,000 tokens
- **Pricing**: $0.22 per 1M input tokens / $0.95 per 1M output tokens (75% off)
- Advanced coding capabilities with massive context window

### **MiniMax M2** - High-Performance Chat

- **Model ID**: `minimax-m2`
- **Provider**: `canopywave/minimax/minimax-m2`
- **Context Window**: 196,608 tokens
- **Pricing**: $0.25 per 1M input tokens / $1.00 per 1M output tokens (75% off)
- Powerful conversational AI with large context support

## 🚀 Getting Started

All models support streaming, tool calling, and JSON output mode:

```bash
curl -X POST https://api.llmgateway.io/v1/chat/completions \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3-coder",
"messages": [{"role": "user", "content": "Write a Python function"}]
}'
```

✅ **75% Discount** - Exclusive pricing for all three models
✅ **Large Context Windows** - 196k-262k tokens
✅ **Full Feature Support** - Streaming, tools, JSON output
✅ **Instant Access** - Available now

---

**[Get started now](/signup)** 🚀
2 changes: 2 additions & 0 deletions packages/models/src/models.ts
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Expand Up @@ -5,6 +5,7 @@ import { googleModels } from "./models/google.js";
import { llmgatewayModels } from "./models/llmgateway.js";
import { metaModels } from "./models/meta.js";
import { microsoftModels } from "./models/microsoft.js";
import { minimaxModels } from "./models/minimax.js";
import { mistralModels } from "./models/mistral.js";
import { moonshotModels } from "./models/moonshot.js";
import { nousresearchModels } from "./models/nousresearch.js";
Expand Down Expand Up @@ -175,6 +176,7 @@ export const models = [
...deepseekModels,
...mistralModels,
...microsoftModels,
...minimaxModels,
...moonshotModels,
...alibabaModels,
...nousresearchModels,
Expand Down
21 changes: 21 additions & 0 deletions packages/models/src/models/alibaba.ts
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Expand Up @@ -578,4 +578,25 @@ export const alibabaModels = [
},
],
},
{
id: "qwen3-coder",
name: "Qwen3 Coder",
family: "alibaba",
providers: [
{
providerId: "canopywave",
modelName: "qwen/qwen3-coder",
inputPrice: 0.22 / 1e6,
outputPrice: 0.95 / 1e6,
discount: 0.75,
requestPrice: 0,
contextSize: 262000,
maxOutput: 8192,
streaming: true,
vision: false,
tools: true,
jsonOutput: true,
},
],
},
] as const satisfies ModelDefinition[];
25 changes: 25 additions & 0 deletions packages/models/src/models/minimax.ts
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@@ -0,0 +1,25 @@
import type { ModelDefinition } from "@/models.js";

export const minimaxModels = [
{
id: "minimax-m2",
name: "MiniMax M2",
family: "minimax",
providers: [
{
providerId: "canopywave",
modelName: "minimax/minimax-m2",
inputPrice: 0.25 / 1e6,
outputPrice: 1.0 / 1e6,
discount: 0.75,
requestPrice: 0,
contextSize: 196608,
maxOutput: undefined,
streaming: true,
vision: false,
tools: true,
jsonOutput: true,
},
],
},
] as const satisfies ModelDefinition[];
Comment on lines +3 to +25

@coderabbitai coderabbitai Bot Nov 8, 2025

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⚠️ Potential issue | 🔴 Critical

🧩 Analysis chain

Verify pricing and discount calculation consistency.

The discount: 0.75 field combined with the current inputPrice and outputPrice values creates a potential inconsistency with the changelog. According to the ProviderModelMapping interface comment in packages/models/src/models.ts (line 48-50), discount represents the discount percentage where 0.5 = 50% off. This means discount: 0.75 indicates 75% off, so the final user-facing price should be base * (1 - 0.75) = base * 0.25.

With the current values:

  • Input: 0.25 / 1e6 with 75% discount = $0.0625 per 1M tokens (final)
  • Output: 1.0 / 1e6 with 75% discount = $0.25 per 1M tokens (final)

However, the changelog (lines 39, 40) states: "$0.25 per 1M input tokens / $1.00 per 1M output tokens (75% off)", which matches the base prices in the code, not the discounted prices.

This same issue affects all three models (GLM-4.6, Qwen3 Coder, and MiniMax M2).

Either:

  1. The inputPrice/outputPrice should be 4x higher (base prices before discount), OR
  2. The changelog should show the lower final prices after discount, OR
  3. The interpretation/calculation of the discount field needs clarification

Please clarify the intended pricing model and ensure consistency between code and documentation. You may want to verify this with the team or check how the discount field is actually applied in the pricing calculation logic elsewhere in the codebase.

🏁 Script executed:

#!/bin/bash
# Search for how the discount field is used in pricing calculations
rg -n -C 5 'discount' --type ts -g '!**/models/**' -g '!**/*.test.ts'

Length of output: 27987

🏁 Script executed:

#!/bin/bash
# Check model definitions with discount field to see if pattern is consistent
rg -n 'discount:' packages/models/src/models --type ts -A 1 -B 1

Length of output: 11177

🏁 Script executed:

#!/bin/bash
# Search for changelog to verify what "$0.25" refers to (base vs final price)
find . -name 'CHANGELOG*' -o -name 'changelog*' -o -name 'CHANGES*' | head -5

Length of output: 327

🏁 Script executed:

#!/bin/bash
# Find and display the changelog entry for minimax pricing
grep -r "0.25\|minimax\|Minimax" ./apps/ui/src/content/changelog -A 5 -B 5 | head -100

Length of output: 2558

🏁 Script executed:

#!/bin/bash
# Also check if there's a specific date/entry mentioning the pricing changes
find ./apps/ui/src/content/changelog -type f -name "*.md*" -o -name "*.ts*" | head -5 | xargs ls -la

Length of output: 604

The pricing calculation is incorrect and will undercharge users by approximately 75%.

The changelog entry for MiniMax M2 explicitly states "$0.25 per 1M input tokens / $1.00 per 1M output tokens (75% off)" — these are the final prices users should pay. However, the code applies the discount as a second multiplier:

final_price = base_price × (1 - discount)
            = (0.25 / 1e6) × (1 - 0.75)
            = (0.25 / 1e6) × 0.25
            = 0.0625 / 1e6

Users would be charged $0.0625 per 1M tokens, not the documented $0.25.

Fix: Adjust inputPrice and outputPrice to represent base prices before discount:

  • inputPrice should be 1.0 / 1e6 (so 1.0 × 0.25 = 0.25 final)
  • outputPrice should be 4.0 / 1e6 (so 4.0 × 0.25 = 1.0 final)

This same issue affects other models with discounts in the codebase (alibaba, zai, etc.).

🤖 Prompt for AI Agents 
In packages/models/src/models/minimax.ts around lines 3 to 25, the configured
inputPrice/outputPrice are already discounted but the code applies the discount
again, resulting in undercharging; change inputPrice to the pre-discount base of
1.0 / 1e6 and outputPrice to 4.0 / 1e6 so that applying discount: base ×
discount (0.25) yields the advertised $0.25/$1.00 per 1M tokens, and audit other
model entries that set a discount to ensure their input/output prices are the
undiscounted base values.

15 changes: 15 additions & 0 deletions packages/models/src/models/zai.ts
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Expand Up @@ -155,6 +155,21 @@ export const zaiModels = [
tools: true,
jsonOutput: true,
},
{
providerId: "canopywave",
modelName: "zai/glm-4.6",
inputPrice: 0.45 / 1e6,
outputPrice: 1.5 / 1e6,
discount: 0.75,
requestPrice: 0,
contextSize: 202752,
maxOutput: undefined,
streaming: true,
reasoning: false,
vision: false,
tools: true,
jsonOutput: true,
},
],
},
{
Expand Down
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