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Granite 4.2 8B vs Hy4 preview

vs
Hy4 preview

Tencent

40#237
Signal-by-Signal Comparison
SignalGranite 4.2 8BDeltaHy4 preview
Capabilities
67
--
67
Pricing
100
+2
98
Context window size
81
-14
96
Recency
100
--
100
Output Capacity
81
+4
77
Overall Result
2 wins
of 5
1 wins
Granite 4.2 8B wins 2 of 5 signals

Score History

Score History (2 data points)
Granite 4.2 8BHy4 preview
Granite 4.2 8B

40

current score

Leader

Tied

right now

Hy4 preview

40

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

Granite 4.2 8B

IBM

Best Value
Per request$0.000175
Daily$0.58
Monthly$17.50
Annual$210.00

Hy4 preview

Tencent

Per request$0.002084
Daily$6.95
Monthly$208.45
Annual$2501.40

Granite 4.2 8B saves you $190.95/month

That's $2291.40/year compared to Hy4 preview at your current usage level of 100K calls/month.

92% cheaper
Choose Granite 4.2 8B for cost optimization

Granite 4.2 8B pricing:
Input:$0.10/M tokens
Output:$0.15/M tokens
Hy4 preview pricing:
Input:$0.83/M tokens
Output:$2.50/M tokens
Tie
Granite 4.2 8B

IBM

40

Composite Score

Tie
Hy4 preview

Tencent

40

Composite Score

Signal-by-Signal Comparison
MetricGranite 4.2 8BHy4 previewWinner
Overall Score
40
40
--
Rank#236#237
Granite 4.2 8B
Quality Rank#236#237
Granite 4.2 8B
Adoption Rank#236#237
Granite 4.2 8B
Parameters8B----
Context Window131K1049K
Hy4 preview
Pricing$0.10/$0.15/M$0.83/$2.50/M--
Signal Scores
Capabilities
67
67
Granite 4.2 8B
Pricing
100
98
Granite 4.2 8B
Context window size
81
96
Hy4 preview
Recency
100
100
Granite 4.2 8B
Output Capacity
81
77
Granite 4.2 8B
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

Granite 4.2 8BEntry Level

Scores 40/100 (rank #236), placing it in the top 19% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Hy4 previewEntry Level

Scores 40/100 (rank #237), placing it in the top 19% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose Granite 4.2 8B when you need:

  • High-volume production workloads where API costs must be minimized
  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model

Choose Hy4 preview when you need:

  • Processing long documents or large codebases (1049K token context)
  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
Granite 4.2 8BBest Value
Input cost$0.10/M tokens
Output cost$0.15/M tokens
Cost per quality point$0.006
Est. monthly (1M tokens/day)$3.75
Hy4 preview
Input cost$0.83/M tokens
Output cost$2.50/M tokens
Cost per quality point$0.083
Est. monthly (1M tokens/day)$50.02

Granite 4.2 8B offers 93% better value per quality point. At 1M tokens/day, you'd spend $3.75/month with Granite 4.2 8B vs $50.02/month with Hy4 preview - a $46.27 monthly difference.

Latency & Speed
Granite 4.2 8BFaster
Speed score0/100
Hy4 preview
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

Granite 4.2 8B

Customer support chatbot

Suitable for user-facing chat with competitive response times. Granite 4.2 8B also offers lower per-token costs for high-volume support

Granite 4.2 8B

Long document analysis

Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass

Hy4 preview

Batch data extraction

Lower output pricing ($0.15/M) reduces costs when processing thousands of records daily

Granite 4.2 8B

Creative writing & content

Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content

Granite 4.2 8B
Which Should You Choose?
Our recommendation:
Granite 4.2 8B

Granite 4.2 8B and Hy4 preview are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

Granite 4.2 8B
Recommended

by IBM

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 93% lower pricing; better value at scale
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale

by Tencent

Consider for specialized use cases.

Capability Comparison
CapabilityGranite 4.2 8BHy4 preview
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoning
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Granite 4.2 8B

IBM

Best Value
$0.3600
estimated monthly cost

Hy4 preview

Tencent

$4.50
estimated monthly cost

Granite 4.2 8B saves you $4.14/month

That's 92% cheaper than Hy4 preview at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterGranite 4.2 8BHy4 preview
Context Window131K1.0M
Max Output Tokens117,96464,000
Open SourceYesNo
CreatedAug 31, 2026Aug 28, 2026
Last updated: 30m ago

相关对比

Granite 4.2 8B vs Hy4 preview (2026) | LM Market Cap