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© 2026 CompareLLM. Public benchmark data aggregated from Arena Elo, LiveBench, SWE-bench & OpenRouter.

Every score has a dated snapshot.

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  3. Claude Opus 4.5 vs AI21: Jamba Large 1.7

Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Claude Opus 4.5 vs AI21: Jamba Large 1.7 benchmark

In this head-to-head showdown, AI21: Jamba Large 1.7 is more budget-friendly at $8/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

Executive Comparison Verdict

Bottom Line: Choose Claude Opus 4.5 if your priority is peak reasoning, complex code generation, and top preference Elo. Choose AI21: Jamba Large 1.7 if you are optimizing for low latency, high throughput, and cost-efficient API deployment.
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Executive Verdict Summary

AI21: Jamba Large 1.7 holds empirical advantage (3 of 3 metrics)

Coding / SWESWE-bench
Claude Opus 4.5Top code solve rate
ReasoningGPQA / Live
Claude Opus 4.5Top logical accuracy
Best Value$/1M Tok
AI21: Jamba Large 1.7Lowest API billing cost
Speed / TokTok/Sec
Claude Opus 4.5Fastest stream rate

Verified Advantage Breakdown

3 benchmarks evaluated across capability, speed, and cost

Claude Opus 4.5 (0)AI21: Jamba Large 1.7 (3)
Claude Opus 4.5
0 of 3 Wins
Competitive baseline across remaining benchmarks
AI21: Jamba Large 1.7
3 of 3 Wins
✓Input price✓Output price✓Context window
Anthropic
Claude Opus 4.5

Anthropic frontier coding and computer-use model. SWE-bench leader on the official mini-SWE-agent harness in the Feb 2026 refresh.

Elo 1,568In: $5 · Out: $25/1M
ai21
Leads 3 of 3
AI21: Jamba Large 1.7

Auto-discovered from OpenRouter (ai21/jamba-large-1.7). Preview until a second source matches.

In: $2 · Out: $8/1M

Claude Opus 4.5 Thinking Depth & Cost Scaler

Model A

Simulate accuracy gains vs added response time & token cost

Mode: Medium (16k budget)

Reasoning models “think before answering” by generating internal reasoning tokens. Higher effort improves math, coding, and logic accuracy, but increases response delay and token costs.

Delay
380 ms
Standard
CoT Tokens
~3,200
Internal reasoning
Cost / 1k
$90.00
9.0× base bill
Accuracy Boost
+5.2%
STEM & Logic
Top Rival Showdowns for Claude Opus 4.5
All Matchups
Compare vs:vs GPT-5vs Gemini 3 Provs Grok 4.6vs DeepSeek V4 Provs Qwen 3 Max
Preference Leader

No shared data

Single model data

Throughput Leader

No shared data

No latency data

Value per Dollar LeaderAI21: Jamba Large 1.7 Wins

AI21: Jamba Large 1.7

$8 / 1M output

Capability Percentiles

Relative percentile scores computed across all active models in the benchmark catalog.

Multi-Dimensional Capability Radar

Leaders Matchup Capability Radar

Comparing top standard models across 6 key capability dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect
0–100 %ile

Overall Matchup Breakdown

Category wins across reasoning intelligence, generation speed, and token cost.

Claude Opus 4.5 (7)vsAI21: Jamba Large 1.7 (3)
Claude Opus 4.5: 7W (70%)Overall: Claude Opus 4.5AI21: Jamba Large 1.7: 3W (30%)
← Claude Opus 4.5AI21: Jamba Large 1.7 →
🏆Claude Opus 4.5 Leads(5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Benchmark
Claude Opus 4.5vsAI21: Jamba Large 1.7
Preference Elo
1,568vs—
Coding Elo
1,574vs—
SWE-bench
76.8%vs—
LiveBench
71.2%vs—
GPQA Diamond
84.1%vs—
Claude Opus 4.5: 5WAI21: Jamba Large 1.7: 0W
🏆Claude Opus 4.5 Leads(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark
Claude Opus 4.5vsAI21: Jamba Large 1.7
Output speed
62 tok/svs—
Time to first token
380 msvs—
Claude Opus 4.5: 2WAI21: Jamba Large 1.7: 0W
🏆AI21: Jamba Large 1.7 Leads(3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark
Claude Opus 4.5vsAI21: Jamba Large 1.7
Output price
$25/1Mvs$8/1M+$17/1M
Input price
$5/1Mvs$2/1M+$3/1M
Context window
200kvs256k+56k
Claude Opus 4.5: 0WAI21: Jamba Large 1.7: 3W

Side-by-Side Benchmark Matrix

Claude Opus 4.5AI21: Jamba Large 1.7
Preference Elo
Claude Opus 4.51,568
AI21: Jamba Large 1.7—
Coding Elo
Claude Opus 4.51,574
AI21: Jamba Large 1.7—
LiveBench
Claude Opus 4.571.2%
AI21: Jamba Large 1.7—
SWE-bench
Claude Opus 4.576.8%
AI21: Jamba Large 1.7—
GPQA Diamond
Claude Opus 4.584.1%
AI21: Jamba Large 1.7—
Time to first token
Claude Opus 4.5380 ms
AI21: Jamba Large 1.7—
Output speed
Claude Opus 4.562 tok/s
AI21: Jamba Large 1.7—
Input priceAI21: Jamba Large 1.7 +$3/1M
Claude Opus 4.5$5/1M
AI21: Jamba Large 1.7$2/1M
Output priceAI21: Jamba Large 1.7 +$17/1M
Claude Opus 4.5$25/1M
AI21: Jamba Large 1.7$8/1M
Context windowAI21: Jamba Large 1.7 +56k
Claude Opus 4.5200k
AI21: Jamba Large 1.7256k
BenchmarkClaude Opus 4.5AI21: Jamba Large 1.7Advantage Delta
Preference Elo
1,568
lmarena · Aug 17, 2026
——
Coding Elo
1,574
lmarena · Aug 17, 2026
——
LiveBench
71.2%
livebench · Aug 17, 2026
——
SWE-bench
76.8%
swebench · Aug 17, 2026
——
GPQA Diamond
84.1%
seed-bootstrap · Aug 1, 2026
——
Time to first token
380 ms
seed-bootstrap · Aug 1, 2026
——
Output speed
62 tok/s
seed-bootstrap · Aug 1, 2026
——
Input price
$5/1M
openrouter · Aug 17, 2026
$2/1M
openrouter · Aug 17, 2026
+$3/1M
Output price
$25/1M
openrouter · Aug 17, 2026
$8/1M
openrouter · Aug 17, 2026
+$17/1M
Context window
200k
openrouter · Aug 17, 2026
256k
openrouter · Aug 17, 2026
+56k

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save 65% with AI21: Jamba Large 1.7
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
Claude Opus 4.5$550.00 / mo
In: $175Out: $375
AI21: Jamba Large 1.7$190.00 / mo
In: $70Out: $120
Estimated Cost Delta

AI21: Jamba Large 1.7 is estimated to save $360.00/month ($4,320/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    AI21: Jamba Large 1.7:Pick AI21: Jamba Large 1.7 when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatAI21: Jamba Large 1.7

Lower output list price ($8/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGAI21: Jamba Large 1.7

Larger window (256k).

Screenshots / visionClaude Opus 4.5

Claude Opus 4.5 is the side marked multimodal in the catalog.

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsinsufficient dataNeed SWE-bench on both sides.
High-volume chatAI21: Jamba Large 1.7Lower output list price ($8/1M).
Voice / low-latency UIinsufficient dataNeed TTFT on both sides.
Long-document RAGAI21: Jamba Large 1.7Larger window (256k).
Screenshots / visionClaude Opus 4.5Claude Opus 4.5 is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news
launchFeb 20, 2026

Claude Opus 4.5 and the Feb 2026 SWE-bench row we still cite

The Feb refresh made 4.5 a coding reference. Newer Opus SKUs exist; this row stays as the dated harness point.

Cast Your Matchup Vote

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK
VS
Anthropic

Claude Opus 4.5

Elo 1,568
SWE-bench76.8%
Speed (tok/s)62 tok/s
Input / 1M Tokens$5/1M
Output / 1M Tokens$25/1M
ai21

AI21: Jamba Large 1.7

Elo n/a
SWE-bench—
Speed (tok/s)256k
Input / 1M Tokens$2/1M
Output / 1M Tokens$8/1M

Frequently Asked Questions

Which is better overall, Claude Opus 4.5 or AI21: Jamba Large 1.7?
We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Claude Opus 4.5 or AI21: Jamba Large 1.7?
SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?
AI21: Jamba Large 1.7 output tokens are $8/1M versus $25/1M. Input prices and retry rates still move the real bill.
Which is faster, Claude Opus 4.5 or AI21: Jamba Large 1.7?
We do not have TTFT for both models.
Which has the larger context window?
AI21: Jamba Large 1.7 accepts 256k tokens versus 200k.
Can I self-host either model?
Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?
No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?
Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Claude Opus 4.5 and AI21: Jamba Large 1.7 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Related news

  • launch · Feb 20, 2026

    Claude Opus 4.5 and the Feb 2026 SWE-bench row we still cite

Similar Head-to-Head Comparisons

All Claude Opus 4.5 matchups →|All AI21: Jamba Large 1.7 matchups →
Claude Opus 4.5 vs Claude Opus 4 (previous opus)Claude Opus 4.5 vs Claude Opus 4.6 (next opus)Claude Sonnet 5 vs Claude Opus 4.5Claude Opus 4.8 vs Claude Opus 4.5Claude Sonnet 4.5 vs Claude Opus 4.5Claude Fable 5 vs Claude Opus 4.5