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Jamba Large 1.7 vs Codestral 2508

Jamba Large 1.7

AI21 Labs

40#323
vs
Codestral 2508

Mistral AI

40#324
Signal-by-Signal Comparison
SignalJamba Large 1.7DeltaCodestral 2508
Capabilities
50
--
50
Pricing
92
-7
99
Context window size
86
--
86
Recency
66
+1
65
Output Capacity
60
+40
20
Overall Result
2 wins
of 5
1 wins
Jamba Large 1.7 wins 2 of 5 signals

Score History

Score History (25 data points)
Jamba Large 1.7Codestral 2508
Jamba Large 1.7

40

current score

Leader

Tied

right now

Codestral 2508

40

current score

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

Jamba Large 1.7

AI21 Labs

Per request$0.006000
Daily$20.00
Monthly$600.00
Annual$7200.00

Codestral 2508

Mistral AI

Best Value
Per request$0.000750
Daily$2.50
Monthly$75.00
Annual$900.00

Codestral 2508 saves you $525.00/month

That's $6300.00/year compared to Jamba Large 1.7 at your current usage level of 100K calls/month.

88% cheaper
Choose Codestral 2508 for cost optimization

Jamba Large 1.7 pricing:
Input:$2.00/M tokens
Output:$8.00/M tokens
Codestral 2508 pricing:
Input:$0.30/M tokens
Output:$0.90/M tokens
Tie
Jamba Large 1.7

AI21 Labs

40

Composite Score

Tie
Codestral 2508

Mistral AI

40

Composite Score

Signal-by-Signal Comparison
MetricJamba Large 1.7Codestral 2508Winner
Overall Score
40
40
--
Rank#323#324
Jamba Large 1.7
Quality Rank#323#324
Jamba Large 1.7
Adoption Rank#323#324
Jamba Large 1.7
Parameters------
Context Window256K256K--
Pricing$2.00/$8.00/M$0.30/$0.90/M--
Signal Scores
Capabilities
50
50
Jamba Large 1.7
Pricing
92
99
Codestral 2508
Context window size
86
86
Jamba Large 1.7
Recency
66
65
Jamba Large 1.7
Output Capacity
60
20
Jamba Large 1.7
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.

Jamba Large 1.7Entry Level

Scores 40/100 (rank #323), placing it in the top -11% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Codestral 2508Entry Level

Scores 40/100 (rank #324), placing it in the top -11% 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 Jamba Large 1.7 when you need:

  • Self-hosted deployments where you need full control over the model

Choose Codestral 2508 when you need:

  • High-volume production workloads where API costs must be minimized
Cost-Performance Analysis
Jamba Large 1.7
Input cost$2.00/M tokens
Output cost$8.00/M tokens
Cost per quality point$0.250
Est. monthly (1M tokens/day)$150.00
Codestral 2508Best Value
Input cost$0.30/M tokens
Output cost$0.90/M tokens
Cost per quality point$0.030
Est. monthly (1M tokens/day)$18.00

Codestral 2508 offers 88% better value per quality point. At 1M tokens/day, you'd spend $18.00/month with Codestral 2508 vs $150.00/month with Jamba Large 1.7 - a $132.00 monthly difference.

Latency & Speed
Jamba Large 1.7Faster
Speed score0/100
Codestral 2508
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

Jamba Large 1.7

Customer support chatbot

Suitable for user-facing chat with competitive response times. Codestral 2508 also offers lower per-token costs for high-volume support

Jamba Large 1.7

Long document analysis

Larger context window (256K tokens) can process longer documents, contracts, and research papers in a single pass

Jamba Large 1.7

Batch data extraction

Lower output pricing ($0.90/M) reduces costs when processing thousands of records daily

Codestral 2508

Creative writing & content

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

Jamba Large 1.7
Which Should You Choose?
Our recommendation:
Jamba Large 1.7

Jamba Large 1.7 and Codestral 2508 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.

Jamba Large 1.7
Recommended

by AI21 Labs

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • 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 Mistral AI

  • Choose for Cost - 88% lower pricing; better value at scale
Capability Comparison
CapabilityJamba Large 1.7Codestral 2508
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)

Jamba Large 1.7

AI21 Labs

$13.20
estimated monthly cost

Codestral 2508

Mistral AI

Best Value
$1.62
estimated monthly cost

Codestral 2508 saves you $11.58/month

That's 88% cheaper than Jamba Large 1.7 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
ParameterJamba Large 1.7Codestral 2508
Context Window256K256K
Max Output Tokens4,096--
Open SourceYesNo
CreatedAug 8, 2025Aug 1, 2025
Last updated: 34m ago

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